I have found that holy place of rest Still changeless .  – Mrs. Hemans – When Mr. Thornton had left the house that morning he was almost blinded by his baffled passion . He was as dizzy as if Margaret , instead of looking , and speaking , and moving like a tender graceful woman , had been a sturdy fish-wife , and given him a sound blow with her fists . He had positive bodily pain – a violent headache , and a throbbing intermittent pulse . He could not bear the noise , the garish light , the continued rumble and movement of the street . He called himself a fool for suffering so ; and yet he could not , at the moment , recollect the cause of his suffering , and whether it was adequate to the consequences it had produced . It would have been a relief to him , if he could have sat down and cried on a door-step by a little child , who was raging and storming , through his passionate tears , at some injury he had received . He said to himself , that he hated Margaret , but a wild , sharp sensation of love cleft his dull , thunderous feeling like lightning , even as he shaped the words expressive of hatred . His greatest comfort was in hugging his torment ; and in feeling , as he had indeed said to her , that though she might despise him , contemn him , treat him with her proud sovereign indifference , he did not change one whit . She could not make him change . He loved her , and would love her ; and defy her , and this miserable bodily pain . He stood still for a moment , to make this resolution firm and clear . There was an omnibus passing – going into the country ; the conductor thought he was wishing for a place , and stopped near the pavement . It was too much trouble to apologise and explain ; so he mounted upon it , and was borne away – past long rows of houses – then past detached villas with trim gardens , till they came to real country hedge-rows , and , by-and-by , to a small country town . Then every body got down ; and so did Mr. Thornton , and because they walked away he did so too . He went into the fields , walking briskly , because the sharp motion relieved his mind . He could remember all about it now ; the pitiful figure he must have cut ; the absurd way in which he had gone and done the very thing he had so often agreed with himself in thinking would be the most foolish thing in the world ; and had met with exactly the consequences which , in these wise moods , he had always fore-told were certain to follow , if he ever did make such a fool of himself . Was he bewitched by those beautiful eyes , that soft , half-open , sighing mouth which lay so close upon his shoulder only yesterday ? He could not even shake off the recollection that she had been there ; that her arms had been round him , once – if never again . He only caught glimpses of her ; he did not understand her altogether . At one time she was so brave , and at another so timid ; now so tender , and then so haughty and regal-proud . And then he thought over every time he had ever seen her once again , by way of finally forgetting her . He saw her in every dress , in every mood , and did not know which became her best . Even this morning , how magnificent she had looked – her eyes flashing out upon him at the idea that , because she had shared his danger yesterday , she had cared for him the least ! If Mr. Thornton was a fool in the morning , as he assured himself at least twenty times he was , he did not grow much wiser in the afternoon . All that he gained in return for his sixpenny omnibus ride , was a more vivid conviction that there never was , never could be , any one like Margaret ; that she did not love him and never would ; but that she – no ! nor the whole world – should never hinder him from loving her . And so he returned to the little market-place , and remounted the omnibus to return to Milton . It was late in the afternoon when he was set down , near his warehouse . The accustomed places brought back the accustomed habits and trains of thought . He knew how much he had to do – more than his usual work , owing to the commotion of the day before . He had to see his brother magistrates ; he had to complete the arrangements , only half made in the morning , for the comfort and safety of his newly imported Irish hands ; he had to secure them from all chance of communication with the discontented work-people of Milton . Last of all , he had to go home and encounter his mother . Mrs. Thornton had sat in the dining-room all day , every moment expecting the news of her son's acceptance by Miss Hale . She had braced herself up many and many a time , at some sudden noise in the house ; had caught up the half-dropped work , and begun to ply her needle diligently , though through dimmed spectacles , and with an unsteady hand ! and many times had the door opened , and some indifferent person entered on some insignificant errand . Then her rigid face unstiffened from its gray frost-bound expression , and the features dropped into the relaxed look of despondency , so unusual to their sternness . She wrenched herself away from the contemplation of all the dreary changes that would be brought about to herself by her son's marriage ; she forced her thoughts into the accustomed household grooves . The newly-married couple-to-be would need fresh household stocks of linen ; and Mrs. Thornton had clothes-basket upon clothes-basket , full of table-cloths and napkins , brought in , and began to reckon up the store . There was some confusion between what was hers , and consequently marked G H T ( for George and Hannah Thornton ) , and what was her son's – bought with his money , marked with his initials . Some of those marked G H T were Dutch damask of the old kind , exquisitely fine ; none were like them now . Mrs. Thornton stood looking at them long – they had been her pride when she was first married . Then she knit her brows , and pinched and compressed her lips tight , and carefully unpicked the G H. She went so far as to search for the Turkey-red marking-thread to put in the new initials ; but it was all used – and she had no heart to send for any more just yet . So she looked fixedly at vacancy ; a series of visions passing before her , in all of which her son was the principal , the sole object – her son , her pride , her property . Still he did not come . Doubtless he was with Miss Hale . The new love was displacing her already from her place as first in his heart . A terrible pain – a pang of vain jealousy – shot through her : she hardly knew whether it was more physical or mental ; but it forced her to sit down . In a moment , she was up again as straight as ever – a grim smile upon her face for the first time that day , ready for the door opening , and the rejoicing triumphant one , who should never know the sore regret his mother felt at his marriage . In all this , there was little thought enough of the future daughter-in-law as an individual . She was to be John's wife . To take Mrs. Thornton's place as mistress of the house , was only one of the rich consequences which decked out the supreme glory ; all household plenty and comfort , all purple and fine linen , honour , love , obedience , troops of friends , would all come as naturally as jewels on a king's robe , and be as little thought of for their separate value . To be chosen by John , would separate a kitchen-wench from the rest of the world . And Miss Hale was not so bad . If she had been a Milton lass , Mrs. Thornton would have positively liked her . She was pungent , and had taste , and spirit , and flavour in her . True , she was sadly prejudiced , and veryignorant ; but that was to be expected from her southern breeding . A strange sort of mortified comparison of Fanny with her , went on in Mrs. Thornton's mind ; and for once she spoke harshly to her daughter ; abused her roundly ; and then , as if by way of penance , she took up Henry's Commentaries , and tried to fix her attention on it , instead of pursuing the employment she took pride and pleasure in , and continuing her inspection of the table-linen . His step at last ! She heard him , even while she thought she was finishing a sentence ; while her eye did pass over it , and her memory could mechanically have repeated it word for word , she heard him come in at the hall-door . Her quickened sense could interpret every sound of motion : now he was at the hat-stand – now at the very room-door . Why did he pause ? Let her know the worst . Yet her head was down over the book ; she did not look up . He came close to the table , and stood still there , waiting till she should have finished the paragraph which apparently absorbed her . By an effort she looked up . " Well , John ? " He knew what that little speech meant . But he had steeled himself . He longed to reply with a jest ; the bitterness of his heart could have uttered one , but his mother deserved better of him . He came round behind her , so that she could not see his looks , and , bending back her gray , stony face , he kissed it , murmuring : " No one loves me – no one cares for me , but you , mother . " He turned away and stood leaning his head against the mantel-piece , tears forcing themselves into his manly eyes . She stood up – she tottered . For the first time in her life , the strong woman tottered . She put her hands on his shoulders ; she was a tall woman . She looked into his face ; she made him look at her . " Mother's love is given by God , John . It holds fast for ever and ever . A girl's love is like a puff of smoke – it changes with every wind . And she would not have you , my own lad , would not she ? " She set her teeth ; she showed them like a dog for the whole length of her mouth . He shook his head . " I am not fit for her , mother ; I knew I was not . " She ground out words between her closed teeth . He could not hear what she said ; but the look in her eyes interpreted it to be a curse – if not as coarsely worded , as fell in intent as ever was uttered . And yet her heart leapt up light , to know he was her own again . " Mother ! " said he , hurriedly , " I can not hear a word against her . Spare me – spare me ! I am very weak in my sore heart ; – I love her yet ; I love her more than ever . " " And I hate her , " said Mrs. Thornton , in a low fierce voice . " I tried not to hate her , when she stood between you and me , because – I said to myself – she will make him happy ; and I would give my heart's blood to do that . But now , I hate her for your misery's sake . Yes , John , it 's no use hiding up your aching heart from me . I am the mother that bore you , and your sorrow is my agony ; and if you do n't hate her , I do . " " Then , mother , you make me love her more . She is unjustly treated by you , and I must make the balance even . But why do we talk of love or hatred ? She does not care for me , and that is enough – too much . Let us never name the subject again . It is the only thing you can do for me in the matter . Let us never name her . " " With all my heart . I only wish that she , and all belonging to her , were swept back to the place they came from . " He stood still , gazing into the fire for a minute or two longer . Her dry dim eyes filled with unwonted tears as she looked at him ; but she seemed just as grim and quiet as usual when he next spoke . " Warrants are out against three men for conspiracy , mother . The riot yesterday helped to knock up the strike . " And Margaret's name was no more mentioned between Mrs. Thornton and her son . They fell back into their usual mode of talk – about facts , not opinions , far less feelings . Their voices and tones were calm and cold a stranger might have gone away and thought that he had never seen such frigid indifference of demeanour between such near relations .


A poem by a resident Life in an Extra Care scheme They said I could n't manage on my own anymore But , where would I go , I really was n't sure I 'm not eating properly , and I 'm having a few falls But I 've lived for many years in those safe and solid walls It 's really very scary , where will I go from here ? Will I be tossed up on the scrap heap ? does anybody care ? I went to look at a nursing home , but that was not for me . People just sat staring at a loud TV . Then some one mentioned Lakeside Court , an independent life With mid day meal provided , to take away the strife . I booked up an appointment , just to go and see If that would be the kind of place , that 's suitable for me . A warm and friendly welcome , met me at the door It helped me to feel comfortable , I wanted to see more It felt so light and airy , a cheerful happy place People that I met that day had a smile upon their face . So here I am , I have my flat , It 's my turn now to smile For I have a place where I can live in independent style No longer am I lonely or afraid that I 'm alone I 've lots of new friends around me and I now called Lakeside ' HOME ' .


26 November 2004 : Andrew Wilbey appointed President of the Society of Dairy Technology 18 November 2004 : Professor Glen Gibson to give University's Christmas Lecture for Children - 20 December 2004 16 November 2004 : Visits to Taiwan help strengthen research links with National Pingtung University of Science and Technology 4 November 2004 : BSc Nutrition and Food Science now recruiting ! 3 November 2004 : " Obesity and health : Is Santa Claus a good role model ? " - Public Lecture on 15 December 2004 2 November 2004 : Prizes for excellent student performances 1 November 2004 : School welcomes visitors from Henan University , China 26 November 2004 : Andrew Wilbey appointed President of the Society of Dairy Technology Andrew Wilbey , a lecturer in the School of Food Biosciences , has been appointed as President of the Society of Dairy Technology . Andrew joined the School of Food Biosciences having worked for several years in the diary industry . At the University he has maintained this specialism with work on dairy products and , in particular , ice cream . The Society of Dairy Technology is dedicated to the advancement of dairy science and technology across all areas of the agri-food sector , to the mutual benefit of milk producers , dairy processors , food retailers and consumers , by the dissemination , and application , of knowledge gained from experience and experiment . Its primary publication is the International Journal of Dairy Technology . For more details of the Society , visit their web site at : http://www.sdt.org / 18 November 2004 : Professor Glen Gibson to give University's Christmas Lecture for Children - 20 December 2004 Each year , the University of Reading hosts a ' Christmas Lecture ' for school children . This year , Professor Glen Gibson , Professor of Food Microbiology in the School of Food Biosciences , is giving the lecture on the 20th December at 3 . 00pm in the University's main Palmer Lecture Theatre in the Palmer Building . The lecture has the title : " Bugs in the Gut " and will include interesting facts about : the trillions and trillions of bacteria inside you what they are about to do to your Christmas dinner how to build models of the human gut how to use diet to feed the friendly flora how to assess the sweetness of the diet and what this does to the germs Update ( 6 December ) : Due to a very high demand , we have been informed that all tickets have now been allocated by the University 16 November 2004 : Visits to Taiwan help strengthen research links with National Pingtung University of Science and Technology A series of symposia are being held as part of the events to mark the 80th anniversary of the founding of the National Pingtung University of Science and Technology , Taiwan . The School has close links with the University through a former PhD student , Dr Mei-Jen Lin . Dr Mike Lewis has just returned from participation in one of the symposia . The subject of his paper was " Raw milk quality and its role in the safety and quality of heat treated milks " . This week , Dr Alistair Grandison is in Taiwan giving a paper on " Manufacture and Purification of Prebiotic Oligosaccharides " and , in early December , Dr Niranjan will also be visiting and giving a paper on " Engineering Challenges in Modern Food Manufacturing " The National Pingtung University has strong research programmes in flavour science , milk stability , prebiotics and probiotics and biotechnology . We hope that the attendance of our staff at these anniversary symposia will further strengthen our relationship with the University . The English version of the University web site can be found at : http://www.npust.edu.tw/english/index.htm 4 November 2004 : BSc Nutrition and Food Science now recruiting ! Official approval has now been given to the launch of our new degree programme - BSc Nutrition and Food Science . Following a detailed scrutiny of our proposed degree by a panel including external assessors , the Faculty Board has given the green light to this expansion of our programmes . The BSc programme will be accepting students from October 2005 . The School has been expanding its work in areas of nutrition and health . We launched our MSc Nutrition and Food Science in 2000 and our increasing activity now enables us to provide an undergraduate programme combining studies in nutrition with our more traditional food science . The combination of the two areas will provide graduates who will be of great value at a time when consumers are increasingly interested in the functional properties of foods . For more details of the new degree programme , please see BSc Nutrition and Food Science 3 November 2004 : " Obesity and health : Is Santa Claus a good role model ? " - Public Lecture on 15 December 2004 A free public lecture is to be given by Professor Christine Williams Professor of Human Nutrition and Head of the School of Food Biosciences here at the University of Reading . The lecture will be given at The Madejski Lecture Theatre Agriculture Building Whiteknights Campus The University of Reading 8 pm Wednesday 15 Dec 2004 The lecture is given in association with the Thames Valley Branch of the British Association for the Advancement of Science Ideally , you should register for the lecture by e-mailing petergraves @ warfieldsberks . f snet . c o . u k . But if you wish you can just turn up 2 November 2004 : Prizes for excellent student performances Congratulations to Chris Armah for winning the student competition for the best presentation at the Oxford Nutrition Group's 10th Anniversary meeting held in Oxford yesterday . Chris is a research assistant studying for a PhD degree . The title of his talk was ' Dietary fat and vascular tone ' . He is working with Dr Anne Marie Minihane . Two of our new second year students have been awarded Prizes as a result of their excellent performance in their Part 1 examinations : Miss Sonam Sanghi , studying Biotechnology , achieved the best results in the Faculty of Life Sciences and was awarded the Ede and Ravenscroft Faculty Prize . Miss Jessica Jin , studying Food Science , achieved the best results for a student on a food related programme and was awarded the Sainsbury's Prize . Congratulations to them all ! 1 November 2004 : School welcomes visitors from Henan University , China As part of our developing link programme with Henan University , the School welcomed 3 members of their staff to the School . Henan University of Technology ( HUT ) , formerly Zhengzhou Institute of Technology , is running a 2 year international programme from which students can progress onto the second year of BSc degree programmes within the School . The first students from this programme will come to Reading in October 2005 . The visit today was part of the preparation for the arrival of the new students . The picture shows ( from left to right ) : Mr Wilbey ( SFB ) , Xaioxi Wang ( Associate Dean and Associate Professor , HUT ) , Lan Kuang ( Vice President and Associate Professor , International College , HUT ) , Professor William s ( Head of School , SFB ) , Professor Lou Yuangong ( Vice President , HUT ) and Dr Gordon ( Director of Teaching and Learning , SFB ) . For more details of this link ,


Nature of problem : The problem treated is the analysis of the effect , on the detected AC signals , of imperfections in and misalignment of the optical components of a polarization-modulation ellipsometer . This permits correction of the values of psi and delta ( characteristics of the sample surface ) for systematic error , estimation of the uncertainty in the final result , and identification of the most significant sources of experimental error . Solution method : The transmitted amplitude vector is computer using the Jones matrices of the individual components . The modified Jones matrices introduced by O ' Handley are used to separate the DC and AC components of the detected intensity . Running time : 1.4 sec for one datum point ( systematic error correction with 5 iterations + complete calculations of experimental uncertainty ) . 0.3 sec for uncertainty calculation only .


Anselm Bourke Mgr Anselm Bourke , born Nicholas Bourke , ( Dublin , 10 September 1835 – West Perth , 2 June 1924 ) was a Roman Catholic priest of Irish origins . He was prominent in Catholic education for several decades , and also founded the West Perth ( now Northbridge ) parish of the Church in 1901 . He made his profession as a Benedictine monk in 1858 , but got dispensation from his monastic vows from the Vatican in 1871 ; therefore , he can not be called a Benedictine . He was still studying to become a priest of the Benedictine order when he arrived in Western Australia on 24 May 1855 aboard the Lady Amhurst with the Spanish Benedictine Father José María Benito Serra OSB - also known as Joseph Serra in Western Australia - , and several other clergymen , mostly Spaniards , but also Irish and French . He made his religious profession on 26 July 1858 , and completed his education and was ordained in 1859 . In 1860 , Bourke was appointed to teach at the Roman Catholic boys' schools at Fremantle and Perth , where he became known as an able scholar and teacher . In 1864 , he was appointed the first parish priest of York – prior to this , the parish had been administered by priests from Toodyay and New Norcia . He lived in simple quarters at the rear of the church and conducted Mass every Sunday . During his time in York , he employed ten ticket of leave men , including three as teachers . Returning to Perth in 1870 , he became the chaplain of Fremantle Prison , and taught at various schools . He got dispensation from his monastic vows on 30 April 4 , 1871 , but his name would still be the one he used in his profession , for which he was known in the Colony , not his birth one . The troublesome years of Bourke , his erratic behaviour and apparent mental problems , his difficult disengagement from the Benedictines and from New Norcia , as well as his temporary exile from Western Australia , ignored by most scholars until now , are mentioned by Dr. Teresa De Castro . In 1885 , he became the first resident priest of the Vasse region at Busselton . In 1889 , on returning to Perth , he became Vicar General for Western Australia serving under Bishop Matthew Gibney , and served voluntarily as New Norcia's agent in Perth , and canvassed the Government for a Roman Catholic representative on the Education Board . He also became active in the debate over state aid to private schools , which had existed since 1871 and had become central to the public debate leading to the June 1894 elections in Western Australia . With the help of three Catholic members of the Legislative Assembly , he founded the Education Defence League to lobby for the continuation of state aid . The normally mild-mannered priest caused some sensation at a public meeting prior to the election by suggesting violence would result if state aid were lifted . The battle was ultimately lost – the MPs who had supported him lost their seats at the election , and in late 1895 the Government passed a bill bringing the funding arrangement to an end . In August 1894 , he resigned as Vicar General , desiring to retire to New Norcia , but changed his mind thereafter , deciding that the number of Catholics arriving in Western Australia due to the gold rush and the cause of maintaining the private schools justified his continued presence . He became Chairman of the Education Board , a position which he held for a number of years . He was also a patron and benefactor of the Sisters of Mercy and financed St Mary's in Leederville and St Brigid's in West Perth , apparently from his own funds . He became a Monsignor in 1898 and the inaugural parish priest for West Perth in 1901 , residing in the Presbytery of St Brigid's in Fitzgerald Street for the rest of his life . He also became involved with the foundation of the University of Western Australia . The Archives of New Norcia keeps an important group of letters addressed from Bourke to the superiors of the monastery , especially to Bishop Rosendo Salvado OSB . Those offer a real portray of Bourke's personality , personal troubles , opinions and interests on relevant matters for his time . This information is completed by the many references to Bourke found in other letters kept in New Norcia Archives , especially in the correspondence between Bishop Martin Griver and Bishop Rosendo Salvado .


Timing Matters : How Social Influence Affects Adoption Pre - and Post-Product Release Sara B. Soderstrom , a Brian Uzzi , b Derek D. Rucker , b James H. Fowler , c Daniel Diermeierd a ) University of Michigan ; b ) Northwestern University ; c ) University of California , San Diego ; d ) University of Chicago Abstract : Social influence is typically studied after a product is released . Yet , audience expectations and discussions begin before a product's release . This observation suggests a need to understand adoption processes over a product's life cycle . To explore pre - and postrelease social influence processes , this article uses survey data from Americans exposed to word of mouth for 309 Hollywood movies released over two and a half years . The data suggest pre - and postrelease social influences operate differently . Prerelease social influence displays a critical transition point with relation to adoption : before a critical value , any level of social influence is negligibly related to adoption , but after the critical value , the relationship between social influence and adoption is large and substantive . In contrast , postrelease social influence exhibits a positive linear relationship with adoption . Prerelease social influence is argued to require more exposures than postrelease social influence because of differences in the diagnosticity and accessibility of the information . To complement the survey data , computational models are used to test alternative hypotheses . Evidence from the computational models supports the proposed model of social influence . Keywords : social influence ; adoption ; prerelease ; diagnosticity ; accessibility Citation : Soderstrom , Sara B. , Brian Uzzi , Derek D. Rucker , James H. Fowler and Daniel Diermeier . 2016 . " Timing Matters : How Social Influence Affects Adoption Pre - and Postproduct Release . " Sociological Science 3 : 915-939 . Received : February 24 , 2016 Accepted : August 21 , 2016 Published : October 24 , 2016 Editor ( s ) : Jesper Sørensen , Gabriel Rossman DOI : 10.15195 / v3 . a40 c 2016 The AuCopyright : thor ( s ) . This open-access article has been published under a Creative Commons Attribution License , which allows unrestricted use , distribution and reproduction , in any form , as long as the original author and source have been credited . c b conversations about companies and their innovations number in the billions . These conversations occur in various venues , from water cooler chatter to social media , but as much as 90 percent remains face-to-face ( Keller and Fay 2012 ) . These conversations allow for social influence to occur . In fact , one survey found that word-of-mouth ( WOM ) influences 70 percent of all buying decisions ( Balter 2008 ) . A single face-to-face conversation can even exert more impact on product judgments than public relations or marketing efforts ( Herr , Kardes , and Kim 1991 ) . These dynamics have led to growing efforts to understand social influence and its effect on corporate and consumer behavior ( Aral and Walker 2011 ; Centola 2011 ; Cialdini and Goldstein 2004 ; Dubois , Rucker , and Tormala 2011 ; Salganik , Dodds , and Watts 2006 ) . Past research has traditionally emphasized " post-release " social influence – communications among consumers and stakeholders that follow their experience with an innovation or product ( Banerjee et al. 2013 ; Foutz and Jank 2010 ; Walgrave and Wouters 2014 ) . For example , early social influence research found that consumers were more likely to adopt a product when they heard about it from a current adopter ( Coleman , Katz , and Menzel 1966 ) . Subsequent research substantiated these effects with a range of explanations , including networks and social proofs ( Goldenberg et al. 2009 ; Mahajan , Muller , and Bass 1990 ; Salganik et al. 2006 ) . Yet , not all social influence is experience based . Social influence occurs throughout D AILY 915 Soderstrom et al. Timing Matters a product's life cycle , including before it is released . For example , social influence can set expectations for actual experiences and subsequent adoption processes ( Banerjee et al. 2013 ; Gopinath , Chintagunta , and Venkataraman 2013 ) . In this regard , prerelease social influence may be critical to postrelease adoption because it can shape expectations , subsequent postrelease conversations , and the size of the early adopter group – key factors predictive of the adoption rate and ultimate market share ( Aral and Walker 2012 ; Salganik et al. 2006 ) . To expand our knowledge of the adoption life cycle , we investigate the relationship between prerelease social influence and adoption patterns . Specifically , we examine a nationwide random sample of Americans exposed to a major form of social influence – direct WOM exchanges with friends and network contacts . We draw on information processing work in psychology to suggest that prerelease WOM might be less accessible and diagnostic than postrelease WOM and that these differences change how WOM influences adoption behavior before and after a product is released . Specifically , based on proposed differences in the diagnosticity and accessibility of information ( Feldman and Lynch 1988 ; Lynch 2006 ) , we predict the relationship between WOM and subsequent adoption differs as a function of whether the WOM occurs during the pre - or postrelease of a product . We present two tests of our hypotheses . First , we test our hypotheses econometrically . These models estimate statistical relationships , functional forms , and effect sizes using proprietary company data on the prerelease WOM , postrelease WOM , and adoption of 309 Hollywood movies released over a two-and-a-half-year period from 1999 – 2001 . Second , we use agent-based models to test whether dynamic person-level and network-level interactions , as outlined by our explanatory framework , account for the adoption rates and functional form patterns of adoption observed in the data . In addition , we evaluate how robust our findings are to alternative specifications . In this way , we seek evidence of the factors associated with pre - and postrelease adoption in equilibrium and the dynamic micro organizational processes that can produce the observed macro equilibrium . Theory Our theoretical predictions draw on information processing and network theories of diffusion . Information processing theory suggests that people are more inclined to act on information when it is accessible and diagnostic ( Feldman and Lynch 1988 ; Lynch 2006 ) . Accessibility refers to whether information is available in a person's mind , whereas diagnosticity refers to whether accessible information is viewed as sufficient to help a person reach a decision consistent with his or her goals ( Lynch 2006 ) . For example , a person deciding whether to purchase a car may have encountered many facts about the car . Not all facts are likely to be equally accessible when she is on the showroom floor . The handling of the car may be salient because of commercial ads , whereas crash test ratings may be less salient . In this example , the accessibility of the handling suggests it will be more likely to influence a person's decision . However , the fact that the handling of the car is salient is not necessarily sufficient for the person to act on this information . She has to decide if the information is diagnostic for the decision at hand . If the handling of sociological science | www.sociologicalscience.com 916 October 2016 | Volume 3 Soderstrom et al. Timing Matters the car is viewed as sufficiently diagnostic , then she may proceed with a purchase ; if this feature is not diagnostic , then she may search her memory for additional information until she is satisfied with the diagnosticity of the accessible information ( Lynch 2006 ) . Several factors can affect the accessibility and the diagnosticity of information ( Feldman and Lynch 1988 ) . For instance , the accessibility of information can be affected by how vivid information is . Vivid information , as compared to pallid information , is more likely to draw initial attention and provoke elaboration that can increase the memory for ( and accessibility of ) that information ( Herr et al. 1991 ; Kisielius and Sternthal 1986 ) . Thus , vividly presented information is more likely to be available to serve as an input to a subsequent adoption decision . Diagnosticity of information can be affected by direct or indirect experience with a product . Direct experience with a product is often more relevant and informative than indirect experience , and thus more diagnostic . For example , individuals were more likely to act on their opinions of food when they tasted it ( direct experience ) versus read about it ( indirect experience ) ( Wu and Shaffer 1987 ) . Indirect experience typically requires greater reinforcement to achieve a similar level of diagnosticity as direct experience . However , while the degree of exposures or number of inputs required may be different , both direct and indirect experiences may eventually surpass the required level of diagnosticity to make an adoption decision ( Lynch 2006 ; Lynch , Marmorstein , and Weigold 1988 ; Wyer and Srull 1986 ) . We propose that social influence in the form of WOM may differ in accessibility and diagnosticity during different stages of a product's life cycle . By definition , prerelease WOM lacks firsthand , trial-based information . Prerelease WOM is based on speculation of what experience with an innovation or product might produce . This dynamic suggests that prerelease WOM lacks the vivid descriptions and testimonial reactions of an innovation or product that come with actual use , reducing the accessibility of prerelease WOM . By definition , the inherently speculative nature of prerelease WOM would seem to render it less diagnostic than postrelease WOM based on product use . Thus , we propose that prerelease WOM is often less diagnostic and less accessible than postrelease WOM . For example , within the movie context , prerelease WOM is likely to possess less vivid descriptions of specific scenes , storylines , and personal reactions to the overall quality of the movie than the same descriptions drawn from movie attendance . Although , on average , prerelease WOM is likely to be less accessible and diagnostic than postrelease WOM , multiple exposures to information can raise its accessibility ( Petrocelli , Tormala , and Rucker 2007 ) . In addition , multiple exposures can also increase a message's diagnosticity . Specifically , even when the validity of a message is unverified , receiving it from multiple individuals can increase belief in the message , an effect observed in experiments ( Salganik et al. 2006 ) , legal decision making ( Waters and Hans 2009 ) , and attitudes in friendship networks ( Fowler and Christakis 2008 ) . As an anecdotal example , National Public Radio's tech news reported that Apple Inc. was releasing a new personal computing product to compete with the Kindle and the Nook , two electronic readers . Even without firsthand information about the product , the station had multiple reports from different sources which appeared sufficient for the station to report the name of Apple's sociological science | www.sociologicalscience.com 917 October 2016 | Volume 3 Soderstrom et al. Timing Matters to-be-released reader as the iSlate . 1 Thus , apparent social agreement may increase the diagnosticity of what was indirect and speculative information , while , at the same time , repeated exposure raises accessibility ( Rosnow and Fine 1976 ; see also Dubois et al. 2011 ) . The implication is that prerelease WOM will require exposure from multiple sources to be as effective as postrelease WOM . Complex contagion theory ( Centola and Macy 2007 ) complements the accessibility and diagnosticity framework ( Feldman and Lynch 1988 ; Lynch 2006 ) . Centola and Macy ( 2007 ) argue that for adoption behaviors that are " costly , risky , or controversial , the willingness to participate may require independent affirmation or reinforcement from multiple sources " ( p. 703 ) . Because no one has adopted an innovation or product prior to release , prerelease WOM is likely to be riskier to act on than postrelease WOM , which contains first-hand information from individuals who have already adopted the new product . Thus , prerelease WOM can be likened to a more complex contagion than postrelease . In this sense , our work connects complex contagion theory and the diagnosticity framework through explaining and specifying an empirical test of how the level of exposure to pre - and postrelease WOM may be related to adoption . Exposure to information is dependent upon on the network of connections among individuals ( Aral and Walker 2011 ; 2012 ; Centola and Macy 2007 ; Dodds and Watts 2004 ) . In social networks , most people have a few friends and a few people have many friends ( Rivera , Soderstrom , and Uzzi 2010 ) . If few people are spreading WOM , chances are it is not coming from the unusual individuals with many contacts but from the individuals with few contacts . As a consequence , WOM is likely to be circulating among contacts in a relatively small number of separate friendship circles of strong ties ( Centola and Macy 2007 ; Valente 2012 ) . However , as the number of people spreading WOM increases , chances rise that the smaller number of highly connected people will be among those spreading WOM ( Onnela and Reed-Tsochas 2010 ) . And , when highly connected people spread WOM , they can spread it to their many weak ties throughout the network , who then circulate it among their contacts in their local friendship circles ( Valente 2012 ) . Put simply , after a critical mass is achieved , the small number of people with many contacts will spread the messages to many separate friendship circles , which produces multiple exposures and thus enhances social influence . For example , Paluck , Shepherd , and Aronow ( 2016 ) found that highly connected students spreading antibullying messages have significantly greater influence in decreasing bullying in middle schools compared to less-connected students sharing the same messages . The preceding discussion suggests that below a critical value of persons spreading WOM , a relatively small number of persons are likely to experience multiple exposures to WOM , but above the critical value , many persons are likely to experience multiple exposures to WOM ( Centola and Macy 2007 ; Dodds and Watts 2004 ; Granovetter 1978 ) . We believe this observation , in conjunction with the notions of accessibility and diagnosticity , suggests that the relationship between adoption and pre - and postrelease WOM differ in several predictable ways . First , the relationship between prerelease WOM and adoption can have two distinct regimes , one before reaching and one after reaching a critical mass of persons spreading WOM in the network . In the first regime , any amount of prerelease WOM before the critical sociological science | www.sociologicalscience.com 918 October 2016 | Volume 3 Soderstrom et al. Timing Matters value is likely to result in negligible increases in adoption in the population . This outcome arises because only a minority of people in the population are hearing WOM from multiple sources ; as such , the majority of the population does not hear WOM at a rate that is likely to meet their accessibility and diagnosticity threshold for adoption . However , after the critical value , the relationship between WOM and adoption is likely to result in significant adoption in the population at all levels of WOM because many people in the population are likely to experience multiple exposures that should facilitate reaching their accessibility and diagnosticity thresholds for adoption . Second , based on the constructs of accessibility and diagnosticity , such a dual regime is less likely for postrelease WOM . Specifically , as postrelease information should be of greater accessibility and diagnosticity , even one exposure to postrelease WOM could be sufficient to surpass an individual's diagnosticity threshold . Because multiple exposures are not needed , this suggests a linear relationship between the amount of WOM and adoption . No critical value exists ; rather , each exposure is likely to prompt an adoption . Thus , comparing the effects of WOM on adoption for the same innovation or product in pre - and postrelease , we expect a critical value dynamic only for prerelease WOM . Formally , we present the three following hypotheses : H1 : A critical value exists that must be met for prerelease WOM to influence innovation adoption . Below this critical value , any level of prerelease WOM has relatively little impact on the level of initial adoption . After WOM is above the critical value , any level of prerelease WOM has a positive effect on adoption . H2 : Small changes around the critical value of prerelease WOM are associated with large differences in adoption . H3 : The effect of postrelease WOM on adoption is independent of a critical value . Postrelease WOM is proportional to adoption at all levels of WOM . Methods Data The movie industry provides a broad basis for theory development and testing ( Cattani et al. 2008 ; Hsu 2006 ; Sorenson and Waguespack 2006 ; Zuckerman et al. 2003 ) . Our data includes 309 Hollywood movies released over a two-and-ahalf-year period between March 1999 and August 2001 . Our tests are based on unique , nonpublic data obtained from a professional survey firm for film production companies and shared with us for research purposes . For each movie , WOM is longitudinally measured in pre - and postrelease phases of adoption life cycle . The survey data records information on respondents' movie-going behavior , movie preferences , and whether they heard WOM about forthcoming and released movies from their family or friends . Respondents were a national random sample chosen through the random digit dialing of over 180,000 respondents . About 300 persons sociological science | www.sociologicalscience.com 919 October 2016 | Volume 3 Soderstrom et al. Timing Matters were contacted each day , Monday through Thursday , from March 1999 to August 2001 , excluding holidays . The survey had a repeated-survey design ; the same items were asked of different respondents on each survey . A professional telephone interviewer led respondents through the survey . First , respondents were asked to indicate all the movies they knew were playing or forthcoming in the cinema . Second , for all the movies the respondents indicated , the respondents were asked whether friends or family were talking about the movie . Third , respondents were asked questions about their movie-going behavior , such as their favorite genre . Because the data is sold to end users who demand reliability , the data is checked for random sampling across demographic and movie-going groups , and respondents are read pick lists that contain fictitious movie titles to gauge respondents' true recall . We merged our survey data with archival data on movie , studio , star , director , and box office characteristics from the Internet Movie Database ( IMDb ) , and Metacritic.com ( Hsu 2006 ; Sorenson and Waguespack 2006 ; Zuckerman et al. 2003 ) . Measures Our dependent variable is movie adoption . Movie adoption was measured as ( 1 ) opening weekend box office and ( 2 ) second weekend box office . Data are from the IMDb and are measured in dollars . Our criterion variables are pre - and postrelease WOM . Prerelease WOM was operationalized as the percentage of respondents who reported that their friends were talking about a particular movie during the Monday – Thursday prior to its release on opening box office weekend . Postrelease WOM was operationalized as the percentage of respondents who reported that their friends were talking about a particular movie during the Monday – Thursday after opening box office weekend but before the second weekend box office . We note that postrelease WOM is likely to still consist of WOM from those who have not directly seen the movie . However , given we are predicting different functional forms , this limitation appears to make our tests more conservative . To infer the level of pre - or postrelease WOM around the average person in the population , we exploited the random sample's ability to estimate a population mean . Because each respondent was randomly sampled , we aggregated the percentage of respondents reporting they heard WOM into a percentage-level variable for that survey and movie . For example , if 20 percent of the sample of people surveyed on a particular day said they had heard WOM about a specific movie , we operationalized the level of WOM for that movie on that day at 20 percent . We controlled for a number of factors known to influence movie consumption ( Basuroy , Chatterjee , and Ravid 2003 ; Eliashberg and Shugan 1997 ; Liu 2006 ; Sorenson and Waguespack 2006 ) . Screens . The number of screens a movie is shown on affects the number of tickets that can be sold . This variable also serves as a proxy for advertising because advertising budgets are designed to fill the available seats ( Elberse and Eliashberg sociological science | www.sociologicalscience.com 920 October 2016 | Volume 3 Soderstrom et al. Timing Matters 2003 ; Sorenson and Waguespack 2006 ) . We measured this variable as the count of the number of screens on which the movie played as reported in IMDb . Critics' reviews . Critics affect film attendance ( Eliashberg and Shugan 1997 ; Zuckerman et al. 2003 ) . Critics' reviews were operationalized by Metacritic.com as a weighted average of all the scores assigned by individual critics to each movie . The scores ranged from 0 to 100 , with higher scores representing better reviews . Well-known critics ( e.g. , Roger Ebert ) and influential publications were more highly weighted than local reviews ( see Metacritic.com for methodological details ) . Percent avid . Avid moviegoers more frequently consume movies and by definition have lower thresholds for attending any movie . To control for avidity , we coded a respondent who saw at least one movie a month as an avid ( De Vany 2004 ) . The proportion of avids was aggregated from the survey responses in the same way as WOM to form a measure of percent avid . Holiday release . Films released during holidays experience greater overall demand for movie tickets and advertising . We coded a movie's release date as reported on IMDb for whether or not it was released during a peak movie-going weekend ( 1 = yes ; 0 otherwise ) . Movie budget . We measured movie budget as the total production costs in dollars , which subsumes the costs of the movie including salaries , studio time , props , and advertising ( Sorenson and Waguespack 2006 ) . Although a line item breakdown of a movie's budget would be ideal to control for the exact level of advertising expenditures , advertising expenditures for movies are not publicly available ( Elberse and Eliashberg 2003 ) . Nevertheless , previous work has shown that a movie's production costs provides a reasonable and widely-used proxy measure for advertising expenses ( Elberse and Eliashberg 2003 ; Gopinath et al. 2013 ; Joshi and Mao 2012 ; Lui 2006 ) . In addition , we use number of screens and holiday release as further proxy measures ( Sorenson and Waguespack 2006 ) as reported from IMDb . Star power . The name recognition of the actors ( i.e. , a bankable star ) can affect a movie's box office . We use the methodology of Basuroy et al. ( 2003 ) to assess star power by how many top fifteen – grossing films in the previous five years starred one of the top three billed actors in a film . If one star had been in a single top-grossing film , another star had been in three top-grossing films , and the third star had been in no top-grossing films , Star Power equaled 4 . Alternative operationalizations , such as assigning star power points for top ten or top twenty – grossing films , produced similar results . Genre . We controlled for the type of movie with an indicator variable using the standard categories of Action / Adventure , Comedies , Dramas , Horror , Sci-Fi , and Family . sociological science | www.sociologicalscience.com 921 October 2016 | Volume 3 Soderstrom et al. Timing Matters Rating . We controlled for the movie's rating with an indicator variable using the standard categories of G , PG , PG-13 , or R. Lagged number of prior adopters . Prior work operationalized social influence in terms of the number of prior adopters ( Cialdini and Goldstein 2004 ) . The number of prior adopters for the second weekend box office was defined as opening weekend box office . By definition , there is no count of prior adopters for prerelease . Descriptive statistics and correlations can be found in the online supplement , appendix 1 . Statistical Model We used ordinary least squares ( OLS ) regression and a spline methodology to test for changes in the relationship between WOM and box office at different levels of WOM . Prerelease WOM was measured the week prior to opening weekend box office , and postrelease WOM was measured between opening weekend box office and second weekend box office . The spline method has three steps . ( 1 ) Because theory does not specify a critical value or position of a critical value , we adopted a conservative method , which segmented WOM's observed range into equidistant length splines at 5 percentile increments ( Long and Freese 2001 ) . ( 2 ) For each cut-point , we determined whether the estimated slope before and after the cut-point were statistically different from each other by computing the difference between the slope before the cut point ( i.e. , slope 1 ) and the slope after the cut point . Statistically significant different slopes ( i.e. , slope difference ) indicate that a critical value is present at which the strength of the relationship between WOM and adoption changes . ( 3 ) To determine which critical value , if any , provides the best fit relative to other critical values or a null relationship of a simple linear model , we used the Bayesian information criterion ( BIC ) statistic ( Kuha 2004 ) . Robust standard errors were used to control for nonhomogeneity in the residuals . Variance inflation factor ( VIF ) statistics had values < 3 . 0 , for which values of 10.0 or more indicate multicollinearity . Results Table 1 presents 8 regressions ( models 1 – 8 ) of opening weekend box office on prerelease WOM levels and control variables . Model 1 is the control variable – only model . Model 2 is the control variable model plus prerelease WOM without a spline segmentation . Our first finding indicates that WOM is positively and significantly related to the level of initial adoption . Highlighting the explanatory power of prerelease WOM on opening box office weekend , model 2 shows that prerelease WOM is positive and significant , and the R-squared is 28 percentage points ( 0 . 72 – 0 . 44 ) greater than the baseline model ( model 1 ) . Our second finding indicates that prerelease WOM is associated with a critical value around which the relationship between prerelease WOM and adoption changes . Prerelease WOM had a smaller effect on adoption until a critical value was reached , after which point increases in the level of WOM were associated with sociological science | www.sociologicalscience.com 922 October 2016 | Volume 3 sociological science | www.sociologicalscience.com 923 0.72 − 16 . 386 † ( 6 . 864 ) − 45 . 213 † ( 11 . 430 ) 0.44 1.559 * ( 0 . 791 ) 9.322 † ( 2 . 636 ) 0.127 † ( 0 . 024 ) − 12 . 427 * ( 5 . 255 ) 0.286 ( 1 . 427 ) 0.171 ( 0 . 447 ) − − 6.138 † ( 1 . 273 ) 22.70 † ( 3 . 324 ) 0.187 † ( 0 . 037 ) − 13 . 128 ( 8 . 449 ) 0.856 ( 1 . 651 ) 0.616 ( 0 . 483 ) − − 94.940 † ( 6 . 962 ) 39.159 * ( 17 . 060 ) 78.423 † ( 18 . 994 ) 2.750 † ( 1 . 012 ) 8.317 † ( 2 . 600 ) 0.131 † ( 0 . 023 ) − 13 . 440 † ( 5 . 145 ) 0.171 ( 1 . 362 ) 0.080 ( 0 . 436 ) − − − 3 . 521 † ( 1 . 023 ) − 17 . 594 * ( 8 . 245 ) 23.8 0.75 Model 3 35th percentile 39.186 † ( 14 . 621 ) 81.093 † ( 17 . 058 ) 2.820 † ( 1 . 031 ) 8.459 † ( 2 . 609 ) 0.134 † ( 0 . 023 ) − 13 . 554 † ( 5 . 151 ) 0.127 ( 1 . 350 ) 0.123 ( 0 . 436 ) − − − 3 . 271 † ( 0 . 976 ) − 18 . 514 * ( 8 . 285 ) 27.5 0.75 26.726 * ( 13 . 411 ) 94.729 † ( 16 . 180 ) 2.827 † ( 1 . 053 ) 8.496 † ( 2 . 617 ) 0.135 † ( 0 . 023 ) − 13 . 569 † ( 5 . 168 ) 0.193 ( 1 . 361 ) 0.113 ( 0 . 436 ) − − − 1 . 818 * ( 1 . 046 ) − 17 . 481 * ( 8 . 478 ) 26.7 0.75 34.888 † ( 11 . 135 ) 94.073 † ( 14 . 817 ) 2.846 † ( 1 . 028 ) 8.512 † ( 2 . 616 ) 0.142 † ( 0 . 023 ) − 14 . 118 † ( 5 . 226 ) 0.334 ( 1 . 358 ) 0.105 ( 0 . 432 ) − − − 2 . 382 * ( 1 . 182 ) − 18 . 365 * ( 8 . 188 ) 31.4 0.76 37.346 † ( 8 . 937 ) 98.588 † ( 15 . 633 ) 2.946 † ( 1 . 066 ) 8.850 † ( 2 . 616 ) 0.144 † ( 0 . 023 ) − 13 . 838 † ( 5 . 202 ) 0.535 ( 1 . 373 ) 0.138 ( 0 . 429 ) − − − 0 . 761 ( 1 . 464 ) − 19 . 962 * ( 8 . 518 ) 34.8 0.76 Threshold Piece-wise Linear Models Model 4 Model 5 Model 6 Model 7 40th 45th 55th 65th percentile percentile percentile percentile 37.310 † ( 8 . 772 ) 99.322 † ( 16 . 495 ) 2.945 † ( 1 . 065 ) 8.809 † ( 2 . 596 ) 0.144 † ( 0 . 023 ) − 13 . 949 † ( 5 . 155 ) 0.530 ( 1 . 369 ) 0.145 ( 0 . 433 ) − − − 0 . 133 ( 1 . 594 ) − 19 . 878 * ( 8 . 515 ) 34.8 0.76 Model 8 70th percentile Note : 309 observations ; robust standard errors in parentheses ; VIF statistics showed there was no multicollinearity bias in the specification ( VIF between 3.2 and 5.5 across all models ) . The categorical controls are not shown for simplicity ; these data can be found in the online supplement . † p < 0.01 ; * p < 0.05 ( two-tailed test of significance ) BIC ' R-squared Constant Genre Rating Spline intercept Star power Holiday release Avidity Critics ' reviews Budget ( sqrt ) Screen ( log ) Prerelease WOM : Slope difference Prerelease WOM : Slope 1 Prerelease WOM Linear Models Model 1 Model 2 Table 1 : Prerelease WOM and first week product adoption . Soderstrom et al. Timing Matters October 2016 | Volume 3 Soderstrom et al. Timing Matters significant increases in the level of adoption . Models 3 – 8 represent these findings as a series of splines . Each model creates a spline for a different percentile of WOM over the observed range of WOM , which was between its 35th and 70th percentile . ( Note the percentiles do NOT correspond to the simple percentage of people hearing WOM . In prerelease , for example , the 35th and 65th percentiles correspond to 10 percent and 21 percent of the persons hearing WOM , respectively . ) Consistent with hypothesis 1 , models 3 – 8 indicate that a spline model statistically significantly fits the data better than does a linear model . The spline coefficients for prerelease WOM : slope 1 and prerelease WOM : slope difference are jointly and statistically significant for spline models 7 and 8 . On average , the effect of prerelease WOM on consumption is almost four times stronger once it exceeds the critical value ( [ WOM : slope difference + WOM : slope 1 ] ÷ WOM : slope 1 ) . The BIC statistic of piecewise model was 34 ( Table 1 , model 7 ) , which provides " strong " evidence that the piecewise model is a better fit than the baseline linear model ( Long and Freese 2001 ) . The BIC statistic indicates that the best fit is the 65th percentile ; beyond the 65th percentile , there are no additional increases in fit . Our third finding is that after the critical value is reached , the association between prerelease WOM and adoption intensifies , as shown by the statistically significant value of prerelease WOM : slope difference . Small changes in the level of prerelease information around the critical value can tip the system from one regime to the other . The large value of prerelease WOM : slope difference substantiates the change in slope that occurs after the critical point . Numerically , model 7 suggests that after the critical value , each one-unit increase in prerelease WOM ( units are in 1 percent point increments from 1 – 100 ) results in a gain of $ 1 . 3 million at the box office . Before the critical value , each one-unit increase in WOM only results in gains of $ 0 . 3 million . Figure 1a plots these relationships . On the x axis is the level of prerelease WOM and on the y axis is the opening box office weekend . Each scatter point on the plot represents a different movie . The plot also indicates that the critical value for this set of movies was approximately at the level of 21 percent WOM in the system . Before this point , each increase in WOM has a small , positive effect on the growth of adopters , but after that critical value , each increase in the percentage of persons spreading WOM is associated with a greater increase in the number of adopters . Our fourth finding is that distinctive WOM dynamics occur for prerelease and postrelease for the same set of products . The relationship between postrelease WOM and adoption does not display a critical value ; rather , the relationship between postrelease WOM and adoption is similar at all levels of WOM . Table 2 shows the effects of regressing second weekend box office on our control variables , as well as opening box office and prerelease WOM . The table of effects indicates that a simple linear model ( Table 2 , model 2 ) provides as good a fit to the data as any spline specification ( Table 2 , models 3 – 8 ) . All models in Table 2 indicate a positive and significant association between postrelease WOM and second weekend box office . Moreover , the BIC statistic comparing the linear model with the spline models consistently produced a negative BIC statistic , a strong indication that there is no critical value of WOM in postrelease , supporting hypothesis 3 . Figure 1c plots these relationships and shows the second weekend box office for the same set of movies sociological science | www.sociologicalscience.com 924 October 2016 | Volume 3 sociological science | www.sociologicalscience.com First Week Box Office ( millions ) 925 0 20 40 60 80 0 20 40 60 0 0 Nurse Betty 0.2 0.2 Notting Hill Spy Kids Never Been Kissed Double Jeopardy ( c ) 0.4 Prerelease WOM ( a ) 0.4 Prerelease WOM X Men Hannibal 0.6 0.6 American Pie 2 Pearl Harbor 0 20 40 60 80 0 0 20 40 60 80 0 Nurse Betty Spy Kids Notting Hill 0.2 0.2 Double Jeopardy American Pie 2 ( d ) 0.4 Postrelease WOM ( b ) 0.4 Postrelease WOM Never been Kissed X Men Pearl Harbor Hannibal 0.6 0.6 Figure 1 : Data distributions for WOM versus adoption . ( a ) Prerelease WOM empirical results , ( b ) postrelease WOM empirical results , ( c ) prerelease WOM simulation results , ( d ) postrelease WOM simulation results . Estimated Box Office ( millions ) Second Week Box Office ( millions ) Estimated Box Office ( millions ) 80 Soderstrom et al. Timing Matters October 2016 | Volume 3 Soderstrom et al. Timing Matters as shown in Figure 1a . The plots indicate that the relationship between postrelease WOM and second weekend box office is linear , consistent with hypothesis 3 . Computational Findings Our empirical tests regressed adoption rates on various levels of pre - and postrelease WOM across different movies and controlled for time-varying covariates . However , a limitation of the empirical data is that it does not allow us to measure a person's infectiousness nor the network structure directly because our person-level observations are randomly sampled nationally , which benefits statistical generalization but does not furnish a direct measure of the friendship network . To address these limitations , we used the above theory to specify agent-based simulations that complement the empirical analyses . The simulations provide a confirmatory analysis of the mechanisms underlying the empirical data and offer tests for the fit and plausibility of alternative mechanisms . If our proposed micro-framework regarding accessibility and diagnosticity holds , we should find that : ( 1 ) the observed functional forms are related to different levels of exposure to WOM in prerelease and postrelease stages of adoption , ( 2 ) a critical value exists for prerelease WOM but not postrelease WOM , and ( 3 ) the observed critical value and the estimated critical value from the simulation are in agreement . The simulations use a social network structure approximated from an actual , typical social network based on the National Longitudinal Study of Adolescent Health ( Add Health ) . These data have been used extensively for the same purpose we use it here ( Fowler and Christakis 2008 ) . 2 Consistent with our empirical analysis , the computational model does not analyze the adoption curve of one product over time but rather the average adoption of multiple movies exhibiting common exposure , informational , and network characteristics . Our simulation model has three steps . First , we " seed " the network with a certain number of persons who can spread WOM . In the prerelease model , the seed levels were assigned by drawing one observation bi from a distribution b of " WOM " ( the subscript i denotes the ith movie to adopt ) , which was taken from the survey data for prerelease WOM . In the postrelease model , a person who has seen the movie in the prerelease WOM model ( i.e. , an adopter ) can spread WOM . Second , we assign each person who can spread WOM a probability of spreading it to one of their contacts in their network . In prerelease , a person can spread WOM to a contact with probability ti , a uniform random distribution between 0.01 and 0.05 . This means the expected number of contacts a person spreads WOM to is ti times the number of contacts he or she has . In postrelease , each person who has seen the movie can spread WOM with probability ri . We assigned a constant ri = 0.15 , the probability that an adopter spreads WOM to a contact . ti and ri were based on research that reported a person's likelihood of spreading WOM about a product before and after its release ( Banerjee , et al. 2013 ; Goldenberg , Libai , Muller , 2001 ) . Third , adoption of a movie is calculated . In our hypothesized prerelease model , a person goes to a movie after they have heard WOM from two or more network contacts . In our hypothesized postrelease model , any person who has not seen the sociological science | www.sociologicalscience.com 926 October 2016 | Volume 3 sociological science | www.sociologicalscience.com 927 0.81 − 4 . 892 ( 6 . 043 ) 0.554 † ( 0 . 024 ) 0.368 ( 0 . 728 ) − 1 . 685 ( 1 . 493 ) 0.044 † ( 0 . 015 ) − 2 . 126 ( 4 . 069 ) 2.038 † ( 0 . 621 ) 0.239 ( 0 . 194 ) − − 0.82 0.474 ( 6 . 015 ) − 12 . 747 ( 7 . 893 ) 0.460 † ( 0 . 035 ) − 0 . 367 ( 0 . 757 ) − 0 . 642 ( 1 . 502 ) 0.037 * ( 0 . 016 ) − 3 . 190 ( 4 . 021 ) 2.022 † ( 0 . 615 ) 0.225 ( 0 . 190 ) − − 26.092 † ( 7 . 965 ) 20.884 ( 14 . 866 ) 6.833 ( 14 . 023 ) − 13 . 168 ( 7 . 958 ) 0.452 † ( 0 . 038 ) − 0 . 196 ( 0 . 820 ) − 0 . 717 ( 1 . 522 ) 0.038 * ( 0 . 016 ) − 3 . 215 ( 4 . 035 ) 2.029 † ( 0 . 619 ) 0.223 ( 0 . 191 ) − − − 0 . 007 ( 0 . 891 ) − 0 . 178 ( 6 . 252 ) − 10 . 9 0.82 Model 3 35th percentile ( 0 . 619 ) 0.225 ( 0 . 191 ) − − − 0 . 343 ( 0 . 902 ) − 0 . 615 ( 6 . 232 ) − 10 . 8 0.82 24.459 ( 13 . 764 ) 4.293 ( 12 . 671 ) − 13 . 322 ( 7 . 962 ) 0.449 † ( 0 . 039 ) − 0 . 199 ( 0 . 819 ) − 0 . 652 ( 1 . 517 ) 0.039 * ( 0 . 016 ) − 3 . 251 ( 4 . 033 ) ( 0 . 617 ) 0.238 ( 0 . 192 ) − − − 0 . 549 ( 0 . 863 ) − 0 . 983 ( 6 . 249 ) − 10 . 4 0.82 25.914 * ( 12 . 443 ) 4.243 ( 11 . 122 ) − 13 . 491 ( 7 . 960 ) 0.444 † ( 0 . 040 ) − 0 . 173 ( 0 . 816 ) − 0 . 583 ( 1 . 518 ) 0.040 * ( 0 . 016 ) − 3 . 240 ( 4 . 030 ) ( 0 . 617 ) 0.230 ( 0 . 191 ) − − − 0 . 126 ( 0 . 840 ) − 0 . 966 ( 6 . 256 ) − 10 . 5 0.82 22.552 * ( 10 . 782 ) 7.669 ( 9 . 705 ) − 13 . 531 ( 7 . 965 ) 0.443 † ( 0 . 040 ) − 0 . 118 ( 0 . 814 ) − 0 . 647 ( 1 . 515 ) 0.040 * ( 0 . 017 ) − 3 . 318 ( 4 . 037 ) ( 0 . 617 ) 0.224 ( 0 . 191 ) − − 0.539 ( 0 . 841 ) − 0 . 747 ( 6 . 265 ) − 10 . 1 0.82 20.287 * ( 9 . 815 ) 7.880 ( 8 . 984 ) − 13 . 265 ( 7 . 977 ) 0.447 † ( 0 . 040 ) − 0 . 115 ( 0 . 812 ) − 0 . 752 ( 1 . 519 ) 0.039 * ( 0 . 016 ) − 3 . 233 ( 4 . 033 ) Threshold Piece-wise Linear Models Model 4 Model 5 Model 6 Model 7 40th 45th 55th 65th percentile percentile percentile percentile ( 0 . 617 ) 0.224 ( 0 . 191 ) − − 0.570 ( 0 . 866 ) − 0 . 514 ( 6 . 275 ) − 10 . 3 0.82 22.027 * ( 9 . 073 ) 6.103 ( 8 . 807 ) − 13 . 640 ( 7 . 978 ) 0.447 † ( 0 . 040 ) − 0 . 164 ( 0 . 810 ) − 0 . 674 ( 1 . 509 ) 0.040 * ( 0 . 016 ) − 3 . 208 ( 4 . 037 ) Model 8 70th percentile Note : 285 observations ; robust standard errors in parentheses ; VIF statistics showed there was no multicollinearity bias in the specification ( VIF between 4.1 and 4.9 across all models ) . The categorical controls are not shown for simplicity ; these data can be found in the online supplement . † p < 0.01 ; * p < 0.05 ( two-tailed test of significance ) BIC ' R-squared Constant Genre Rating Spline intercept Star power Holiday release Avidity Critics ' reviews Budget ( sqrt ) Box office performance ( lag ) Screen ( log ) Prerelease WOM Postrelease WOM : Slope difference Postrelease WOM : Slope 1 Postrelease WOM Linear Models Model 1 Model 2 Table 2 : Postrelease WOM and second week product adoption . Soderstrom et al. Timing Matters October 2016 | Volume 3 Soderstrom et al. Timing Matters movie but who has heard WOM from at least one contact postrelease goes to the movie . In all WOM models , we assume that a fraction of the population goes to the movie because of idiosyncratic factors that are constant in pre - and postrelease ( Gopinath , et al. 2013 ; Valente 2012 ) using an error term ei drawn from a log normal distribution ( to avoid negative values ) with mean = 0.0025 and variance = 0.00004 . In each model , we add up all of the people who have gone to a movie to calculate the total adoption . To estimate the level of adoption from box office sales , we assume a potential movie audience of 300 million people and a ticket cost of $ 6 each , the average of 1999 – 2001 ticket prices in the United States ( see online supplement , appendix 2 , for further details and code ) . Robustness Checks We included tests of alternative mechanisms from the literature ( e.g. , Centola and Macy , 2007 ; Goldenberg et al. 2001 ) . Alternative A. In prerelease , the adoption decision rule changes from the hypothesized relationship to hearing WOM from one or more contacts . This model reflects more standard adoption rules in which pre - and postrelease WOM both act as simple contagions with higher levels of accessibility and diagnosticity . Alternative B. In postrelease , the adoption decision rule changes from the hypothesized relationship to hearing WOM from two or more contacts . This model reflects a more complex contagion with a higher threshold for accessibility and diagnosticity prior to adoption in both pre - and postrelease stages . Alternative C. In pre - and postrelease , the adoption decision rules change from the hypothesized relationships to hearing WOM from three or more , four or more , five or more , or a random number of contacts , or from 10 percent , 25 percent , 50 percent , 75 percent , and 100 percent of their contacts . These models test for differences in adoption thresholds . Alternative D. In the hypothesized models , the number of contacts ( i.e. , degree ) of individuals in the network varies per the empirical distributions of degree found in the Add Health data ( range 1 to 10 connections ) . Here , we change the size of individual networks so degree is fixed for all individuals in the network at two , four , six , or eight connections and follows the hypothesized decision rules . Results Figure 1 displays scatter plots of the visual agreement between the observed and simulation data for prerelease ( left panel ; Figure 1a , 1c ) and postrelease ( right panel ; Figure 1b , 1d ) , respectively . Consistent with our framework and regression analyses , the simulations' results closely mirror the same functional relationship found in the empirical data . The simulations estimated a weak relationship between the sociological science | www.sociologicalscience.com 928 October 2016 | Volume 3 Soderstrom et al. Timing Matters level of prerelease WOM and adoption between the values of ∼ 5 percent to ∼ 21 percent WOM . After a critical level of prerelease WOM , the simulation shows that each increase in prerelease WOM is associated with large increases in adoption . The pattern of weak and then strong effects before and after the critical value , as well as the critical value itself , correspond closely to the empirical results . By contrast , postrelease WOM does not display the same effects . Postrelease WOM is proportionally associated with adoption , both empirically and in the simulation . These results offer confirmatory support to the findings of the empirical analysis . Alternative models A – D further support our hypothesized model . Across all models , formal tests indicated that the hypothesized model fit the observed data the best . Simulation results are displayed in Figures 2 and 3 . Figure 2 shows that the hypothesized threshold of two persons in prerelease ( Figure 2a ) and one person in postrelease ( Figure 2b ) fits the data better than other specifications . For example , alternative model A for prerelease overestimated opening box office adoption by more than 200 percent . Figure 3 shows that the critical network threshold is robust to changes in the size of a person's network . The best fit is for 4 degrees for prerelease ( Figure 3a ) , which corresponds to the average size of a person's network in the Add Health network data ; postrelease results ( Figure 3b ) are less conclusive but generally consistent with our hypothesized model . Formal tests bore out these results . We took the mean and the variance of the empirical data at 10 percent intervals of WOM and compared those observed values with the values generated by each alternative model specification . Specifically , we evaluated the fit of all models using the χ2 test , which measures the sum of squared errors between the model and observed values for each of the bins , both for the means and the variances . We fitted the data to a Landau distribution , which accounts for the long tail of box-office returns that skew toward lower levels in each bin ( Landau 1944 ) . Table 3 displays the results of these robustness checks . The hypothesized model fits the prerelease data with a χ2 of p = 96 percent and postrelease of p = 88 percent . The model that uses a constant degree of 4 also agrees well with prerelease data χ2 of p = 94 percent but poorly in postrelease of p = 23 percent . These alternative models further support a prerelease individual threshold for adoption of hearing WOM from two or more contacts . The next best fit for a postrelease alternative model was alternative C ( random distribution of individual thresholds with mean threshold of 1 ) with p = 55 percent , which suggests that in postrelease there may be more variation in individual thresholds , with some individuals still wanting to hear from two or more individuals before adopting , but this does not represent the adoption behavior as well as our hypothesized model . These findings indicate that the mechanisms outlined in our framework offer a plausible explanation for how micro behaviors of spreading and hearing preand postrelease social influence within networks can generate the observed macro patterns of adoption . Discussion As noted at the outset of this article , WOM appears to be of increasing interest to both academics and practitioners . However , prior research has not systematically sociological science | www.sociologicalscience.com 929 October 2016 | Volume 3 Soderstrom et al. Timing Matters 70 empirical 2 - hypothesized 3 4 5 60 Box Office ( millions ) 50 40 30 20 10 0 0-0 . 1 0 . 1-0 . 2 0 . 2-0 . 3 Prerelease WOM 0 . 3-0 . 4 0 . 4-0 . 5 ( a ) 45 40 Box Office ( millions ) 35 empirical 1 - hypothesized 2 3 4 5 30 25 20 15 10 5 0 0-0 . 1 0 . 1-0 . 2 0 . 2-0 . 3 Postrelease WOM 0 . 3-0 . 4 0 . 4-0 . 5 ( b ) Figure 2 : ( a ) Opening weekend box office : empirical results compared to simulation outcomes for varying thresholds . ( b ) 2nd weekend box office : empirical results compared to simulation outcomes for varying thresholds . Note : The vertical lines represent the 1-sigma uncertainty in the empirical data within that range of WOM . sociological science | www.sociologicalscience.com 930 October 2016 | Volume 3 Soderstrom et al. Timing Matters 80 empirical degree 2 degree 4 degree 6 degree 8 70 Box Office ( millions ) 60 50 40 30 20 10 0 0-0 . 1 0 . 1-0 . 2 0 . 2-0 . 3 Prerelease WOM 0 . 3-0 . 4 0 . 4-0 . 5 ( a ) 80 70 Box Office ( millions ) 60 empirical degree 2 degree 4 degree 6 degree 8 50 40 30 20 10 0 0-0 . 1 0 . 1-0 . 2 0 . 2-0 . 3 Postrelease WOM 0 . 3-0 . 4 0 . 4-0 . 5 ( b ) Figure 3 : ( a ) Opening weekend box office : empirical results compared to simulation outcomes for varying individual network sizes . ( b ) 2nd weekend box office : empirical results compared to simulation outcomes for varying individual network sizes . Note : The vertical lines represent the 1-sigma uncertainty in the empirical data within that range of WOM . sociological science | www.sociologicalscience.com 931 October 2016 | Volume 3 sociological science | www.sociologicalscience.com 932 Alternative C : Test robustness to individual thresholds as number of contacts and percent of contacts 3 + Pre - and postrelease : Threshold Underestimating adoption in pre - and postre = 3 or more lease 4 + Pre - and postrelease : Threshold Underestimating adoption in pre - and postre = 4 or more lease 5 + Pre - and postrelease : Threshold Underestimating adoption in pre - and postre = 5 or more lease Random distribution Prerelease : Mean threshold = 2 , Overestimating adoption in prerelease of individual threshold postrelease : Mean threshold = 1 10 % + Pre - and postrelease : Overestimating adoption for prerelease Threshold = 10 % of contacts Overestimating adoption for low levels of WOM in postrelease 25 % + Pre - and postrelease : Overestimating adoption for prerelease Threshold = 25 % of contacts Underestimating adoption for higher levels of WOM in postrelease < 5 % 55 % < 5 % < 5 % < 5 % < 5 % < 5 % < 5 % < 5 % < 5 % < 5 % < 10 % 88 % 88 % < 5 % 96 % Alternative B : Test baseline with threshold of 2 in both pre - and postrelease 2 + Pre - and postrelease : Threshold Underestimating adoption in postrelease = 2 or more 96 % < 5 % Consistent with empirical data Qualitative Comparison to Empirical Data Simulation Fit to Empirical Data : Probability of Fit for χ2 Prerelease : Postrelease : Alternative A : Test baseline with threshold of 1 in both pre - and postrelease 1 + Pre - and postrelease : Threshold Overestimating adoption in prerelease = 1 or more Hypothesized Model : Test proposed mechanisms Hypothesized Prerelease : Threshold = 2 or more Mechanisms Postrelease : Threshold = 1 or more Model Condition : Simulation Mechanisms Table 3 : Simulation models overview . Soderstrom et al. Timing Matters October 2016 | Volume 3 sociological science | www.sociologicalscience.com 933 Alternative D : Sensitivity Analysis of Individual Network Size Degree of 2 Prerelease : Threshold = 2 or more Postrelease : Threshold = 1 or more Degree of 4 Prerelease : Threshold = 2 or more Postrelease : Threshold = 1 or more Degree of 6 Prerelease : Threshold = 2 or more Postrelease : Threshold = 1 or more Degree of 8 Prerelease : Threshold = 2 or more Postrelease : Threshold = 1 or more Threshold = 100 % of contacts Pre - and postrelease : Threshold = 75 % of contacts Pre - and postrelease : 75 % + 100 % Pre - and postrelease : Threshold = 50 % of contacts 50 % + Model Condition : Simulation Mechanisms Table 3 continued . Overestimating adoption in pre - and postrelease Overestimating adoption in pre - and postrelease Underestimating adoption in pre - and postrelease Consistent with empirical data Overestimating adoption for prerelease Underestimating adoption for higher levels of WOM in postrelease Overestimating adoption for prerelease Underestimating adoption in postrelease Overestimating adoption for low levels of WOM in prerelease Underestimating adoption in postrelease Qualitative Comparison to Empirical Data < 5 % < 5 % 22 % 23 % 94 % 37 % < 5 % < 5 % < 5 % < 5 % < 10 % < 5 % < 5 % < 5 % Simulation Fit to Empirical Data : Probability of Fit for χ2 Prerelease : Postrelease : Soderstrom et al. Timing Matters October 2016 | Volume 3 Soderstrom et al. Timing Matters compared pre - and postrelease WOM to their social influence . In this article , we tackled this issue using large-scale , real-world empirical data on movie adoption accompanied by an agent-based model . Our results demonstrate that life cycle stage matters : pre - versus postrelease WOM follow distinctive patterns of potential theoretical and practical importance . Theoretically , we introduce the notion of a functional form difference between pre - and postrelease WOM and adoption . For prerelease WOM , until a critical value of WOM is reached , only a small , positive relationship between social influence and adoption is present . However , after this critical value of WOM is reached , every increase in WOM correlates with a significant and large increase in adoption . In contrast , for postrelease WOM , the relationship between WOM and adoption follows a single linear functional form . These patterns were supported by time-series data and agent-based models . Together , these findings suggest the importance of distinguishing and studying preversus postrelease WOM with respect to social influence and adoption . We draw upon an accessibility – diagnosticity framework to explain these functional forms and adoption patterns . The framework focuses on how differences in information and the transfer of information in a network are associated with socially induced adoption . We reasoned that prerelease WOM is based on speculation , hearsay , and other secondhand information that does not appear to significantly affect adoption until sufficient repeated exposure increases the accessibility and diagnosticity of the information . This level of exposure is obtained when potential adopters have the information echoed throughout their network by multiple contacts , which occurs when a sufficient number of highly connected persons in a social network relay prerelease WOM across otherwise disconnected social network clusters . By contrast , because postrelease WOM is more likely to be based on firsthand and direct experience , a single exposure can be sufficient to provide the required accessibility and diagnosticity to prompt adoption . We suggest prerelease WOM acts as a more complex contagion than postrelease WOM because of differences in accessibility and diagnosticity across a product's life cycle . Our work complements and extends that of Centola and Macy ( 2007 ) . Using simulations , Centola and Macy found that complex contagions saturate a network more slowly over time than simple contagions . We extend this work by looking at a snapshot of adoption levels for many different products ( movies ) at one time ( either pre - or postrelease ) . We find a critical point for the influence of a complex contagion ( prerelease WOM ) on adoption but a linear relationship for a simple contagion ( postrelease WOM ) . Further , our empirical analysis suggests that a contagion as " simple " as WOM can change across a product's life cycle stages as it moves from complex to simple . Future research should explore how the role of weak ties may change over time for product adoption as the complexity of contagion changes . We also advanced theory by emphasizing the importance of studying interactions between individual and network thresholds . Prior models have investigated the implications of different individual thresholds on adoption ( Dodds and Watts 2004 ; Granovetter 1978 ) . By contrast , we emphasized the predictive value of a global network – level threshold . Unless this global network reaches a certain threshold of prerelease social influence , negligible changes exist in adoption behavior by consumers . Furthermore , we found a key link : a global network threshold occurred sociological science | www.sociologicalscience.com 934 October 2016 | Volume 3 Soderstrom et al. Timing Matters when individual thresholds for adoption were responsive to exposures or greater WOM . Future research might turn to examine how individual-level thresholds influence this global threshold . The importance of prerelease social influence has a number of potential implications for management research . Consumer trends highlight continued growth in social influence as processes for generating and sharing information about products continue to expand via interpersonal and social media ( Aral and Walker 2011 ) . The present work suggests that managers should move beyond questions of how social influence spreads and seek to understand how influence patterns differ based on the life cycle of an innovation or product : pre - versus postrelease stages . Indeed , were managers to rely only on relationships or observations of postrelease social influence , they may be poorly equipped to make decisions that involve prerelease marketing efforts . Improvement in practice may further occur if future research investigates a broader range of products to identify how critical values vary across product categories and how sensitive the critical value is to change in the level of prerelease social influence before and after the critical value . On a related point , our research suggests the possibility of different interventions as a function of pre - versus postrelease of a product . Prior to a product's release , marketers might focus on encouraging communications among a smaller number of diverse consumers to increase the chance that multiple sources of influence are enacted in the network to foster initial levels of adoption . However , in postrelease , marketers might focus more heavily on getting people to hear about one person's experience with the product , as that one experience may be enough to foster adoption . In addition , during the prerelease phase , failure to have the required level of social influence may also indicate that release should be postponed until prerelease social influence reaches the desired value . Our study uses survey data on face-to-face WOM , which remains a central form of consumer behavior ( Bond et al. 2012 ; Keller and Fay 2012 ) . However , the data are older and censor most of the smallest-budget movies released during that timeframe . Therefore , generalization to current conditions should be done with caution . This limitation recognized , a benefit of the timing for the survey is that it is before the advent of social media sites and therefore likely captured interpersonal WOM . Currently , Facebook and other social media channels complement traditional faceto-face WOM ( Aral and Walker 2011 ; De Bruyn and Lilien 2008 ) . This introduces a new question with respect to how social influence , as measured by WOM , may have changed over time as people hear about products via face-to-face and social media WOM . We suspect that the accessibility , diagnosticity , and complexity of WOM often varies for a phone call compared to a FaceBook post , for example . Future research should explore how the different channels of pre - versus postrelease social influence affect each other as well as consumption behavior . In all cases , a broader and more complete understanding of social influence is acquired by understanding how it operates in different stages of an innovation's life cycle . sociological science | www.sociologicalscience.com 935 October 2016 | Volume 3 Soderstrom et al. Timing Matters Notes 1 The real name was , of course , the iPad . 2 Add Health's initial wave of the study utilized a sampling design that resulted in a nationally representative sample that included participation from 145 middle , junior high , and high schools ; from those schools , 90,118 students completed a 45-minute questionnaire . Each school becomes a full network within the overall Add Health network . In these networks , the number of outward nominations is restricted to 10 because of the procedure used by Add Health . 90.0 percent of subjects named fewer than the maximum , indicating that the degree of each person's network is probably not truncated by the instrument . The average number of friends of a person is 3.8 ( SD = 3.7 ) . References Aral , Sinan , and Dylan Walker . 2011 . " Creating Social Contagion through Viral Product Design : A Randomized Trial of Peer Influence in Networks . 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Fine . 1976 . Rumor and Gossip : The Social Psychology of Hearsay . New York : Elsevier . Salganik , Matthew J. , Peter Sheridan Dodds , and Duncan J. Watts . 2006 . " Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market . " Science 311 ( 5762 ) : 854-856 . http://dx.doi.org/10.1126/science.1121066 Sorenson , Olav , and David M. Waguespack . 2006 . " Social Structure and Exchange : SelfConfirming Dynamics in Hollywood . " Administrative Science Quarterly 51 ( 4 ) : 560-589 . Valente , Thomas W. 2012 . " Network Interventions . " Science 337 ( 6090 ) : 49-53 . http://dx.doi . org / 10 . 1126 / science . 1217330 Walgrave , Stefaan , and Ruud Wouters . 2014 . " The Missing Link in the Diffusion of Protest : Asking Others . " American Journal of Sociology 119 ( 6 ) : 1670-1709 . http://dx.doi.org/10. 1086 / 676853 Waters , Nicole L. , and Valerie P. Hans . 2009 . " A jury of one : Opinion formation , conformity , and dissent on juries . 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" American Journal of Sociology 108 ( 5 ) : 1018-1073 . http://dx.doi.org/10.1086/377518 Acknowledgements : This research was sponsored by the Northwestern University Institute on Complex Systems , the Army Research Laboratory under Cooperative Agreement Number W911NF-09-2-0053 , and the Defense Advanced Research Projects Agency grant BAA-11-64 , Social Media in Strategic Communication . The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies , either expressed or implied , of the Army Research Laboratory or the U.S. government . Sara B. Soderstrom : Organizational Studies and Program in the Environment , University of Michigan . E-mail : capasb@umich.edu . Brian Uzzi : Management and Organizations , Kellogg School of Management , Northwestern University . E-mail : uzzi@kellogg.northwestern.edu . Derek D. Rucker : Marketing , Kellogg School of Management , Northwestern University . E-mail : d-rucker@kellogg.northwestern.edu . James H. Fowler : Political Science , University of California , San Diego . E-mail : fowler@ucsd.edu . Daniel Diermeier : Provost , The University of Chicago . E-mail : ddiermeier@uchicago.edu . sociological science | www.sociologicalscience.com 939 October 2016 | Volume 3


You can do anything when you hit 18 I was downcast after Doncaster , but my longest run so far -- in a respectable time -- has put a spring in my step ( and an ache in the rest of me ) . In this mood , I could run all the way to London and still get round the marathon course . I 'm pleased to say that this week things have improved . I managed to run 18 miles on Saturday and that was quite comfortable . It 's cheered me up to know that the Doncaster half-marathon last week was such a disaster because I was ill , not because I was unfit . That one long run has given my confidence a boost and I 'm convinced I 'll now survive London . It was n't particularly fast -- three hours 21 minutes to be exact -- but at least I know I can do it . Doncaster put some doubt in my mind but I 've bounced back -- in fact it 's spurred me on . I 'm looking forward to the next few weeks of training and I 'm hoping to speed up a bit . I do n't think I 'll be challenging Paula Radcliffe but hopefully I might break five hours . That 's my goal and now I 'm back to my usual cheery self I 'm determined to do it . Liz Champion is the editor of Epilepsy Today