bluuebunny/crossref_metadata_2025 huggingface dataset:
Acting the Part
Authors: Arif Ahmer , Stewart Leo Graiden , Starbird Kate
Published: November 2018

This research examines how Russian disinformation actors participated in a highly charged online conversation about the #BlackLivesMatter movement and police-related shootings in the USA during 2016. We first present high-level dynamics of this conversation on Twitter using a network graph based on retweet flows that reveals two structurally distinct communities. Next, we identify accounts in this graph that were suspended by Twitter for being affiliated with the Internet Research Agency, an entity accused of conducting information operations in support of Russian political interests. Finally, we conduct an interpretive analysis that consolidates observations about the activities of these accounts. Our findings have implications for platforms seeking to develop mechanisms for determining authenticity---by illuminating how disinformation actors enact authentic personas and caricatures to target different audiences. This work also sheds light on how these actors systematically manipulate politically active online communities by amplifying diverging streams of divisive content.
Departing and Returning
Authors: Baumer Eric P. S. , Sun Rui , Schaedler Peter
Published: November 2018

Recent work has identified a variety of motivations for various forms of technology use and non-use. However, less work has closely examined relationships between those motivations and the experiences of transiting among these different forms of use and non-use. This paper fills that gap by conducting a qualitative interview- and diary-based study where participants were asked to deactivate their Facebook account. An abductive analysis suggests participants' experiences can be organized under the conceptual umbrella of sense of agency, which refers to an individual's perception that their actions are under their own control. The analysis shows how, across disparate motivations, all participants took actions that increased their own subjective sense of agency, regardless of whether they returned to Facebook or not. The discussion applies this conceptual lens to prior studies of technology use and non-use. Doing so shows how sense of agency may provide an organizing orientation for understanding subjective experiences of use and non-use.
Efficient Crowd Exploration of Large Networks
Authors: Berenberg Daniel , Bagrow James P.
Published: November 2018

Accurately and efficiently crowdsourcing complex, open-ended tasks can be difficult, as crowd participants tend to favor short, repetitive "microtasks". We study the crowdsourcing of large networks where the crowd provides the network topology via microtasks. Crowds can explore many types of social and information networks, but we focus on the network of causal attributions, an important network that signifies cause-and-effect relationships. We conduct experiments on Amazon Mechanical Turk (AMT) testing how workers can propose and validate individual causal relationships and introduce a method for independent crowd workers to explore large networks. The core of the method, Iterative Pathway Refinement, is a theoretically-principled mechanism for efficient exploration via microtasks. We evaluate the method using synthetic networks and apply it on AMT to extract a large-scale causal attribution network. Worker interactions reveal important characteristics of causal perception and the generated network data can help improve our understanding of causality and causal inference.
Supporting Collaboratively Constructed Independence
Authors: Buyuktur Ayse G. , Hung Pei-Yao , Newman Mark W. , Ackerman Mark S.
Published: November 2018

Independence is a central concern for people in the care of many chronic conditions. It is often viewed as a goal that can be facilitated with the use of patient data. It is also viewed, especially from the medical side, as something an individual achieves. However, in the lived experience, independence is often a set of collaborative practices. In this paper, we unpack findings from an interview-based study of Spinal Cord Injury (SCI) self-care. We found that independence - both functional and in the form of effecting agency - must be co-constructed by the choices and activities of the care network, including the person with disability, caregivers, and clinicians. This collaboratively shaped independence also affects potential collection and use of data in support of self-care. We describe how collaboratively shaped independence informs requirements and constraints for the design of sensor-based networks for self-care in long-term chronic disability.
Investigating Crowd Creativity in Online Music Communities
Authors: Calefato Fabio , Iaffaldano Giuseppe , Lanubile Filippo , Maiorano Federico
Published: November 2018

Crowd creativity is typically associated with peer-production communities focusing on artistic products like animations, video games, and music, but less frequently to Open Source Software (OSS), despite the fact that also developers must be creative to come up with new solutions to their technical challenges. In this paper, we conduct a study to further the understanding of which factors from prior work in both OSS and art communities are predictive of successful collaboration - defined as reuse of previous songs - in three different songwriting communities, namely Songtree, Splice, and ccMixter. The main findings from this study confirm that the success of collaborations is associated with high community status of recognizable authors and low degree of derivativity of songs.
MechanicalHeart
Authors: Callaghan William , Goh Joslin , Mohareb Michael , Lim Andrew , Law Edith
Published: November 2018

Listening to heart sounds is an important first step in evaluating the cardiovascular system and is important in the early detection of cardiovascular disease. We present and evaluate a framework for combining machine learning algorithms, crowd workers, and experts in the classification of heart sound recordings. The development of a hybrid human-machine framework is motivated by the past success in utilizing human computation to solve problems in medicine and the use of human-machine frameworks in other domains. We describe the methods that decide when and how to escalate the analysis of heart sounds to different resources and incorporate their decision into a final classification. Our framework was tested with a combination of machine classifiers and crowd workers from Amazon's Mechanical Turk. The results indicate a hybrid approach achieves greater performance than a baseline classifier alone, utilizing less expert resources while achieving similar performance, compared to a framework without the crowd.
Beyond Lingua Franca
Authors: Chen Mei-Ling , Yamashita Naomi , Wang Hao-Chuan
Published: November 2018

When multiple non-native speakers (NNSs) who share the same native language join a group discussion with native speakers (NSs) of the common language used in the discussion, they sometimes switch back and forth between common language and their native language to reach common ground. However, such code-switching makes others feel excluded and thus not considered appropriate during formal meetings. To offer NNSs more flexibility to code-switch in a group discussion while minimizing the cost of excluding others, we introduced a language support tool that automatically detects a user's spoken language, and then transcribe as well as translate them into another language (common language or NNS's native language). In a within-subject study involving 19 quads (two Japanese and two Chinese) in a collocated setting, participants were asked to perform a series of decision-making tasks with and without the tool. Results showed that the language support tool encouraged diverse use of language during a meeting, resulting in more participation from NNSs - they increased active initiating behaviors from NNSs. Although the perceived quality of collaboration became lower, it also elicited helping behaviors among the NNS pairs.
Crowd Coach
Authors: Chiang Chun-Wei , Kasunic Anna , Savage Saiph
Published: November 2018

Traditional employment usually provides mechanisms for workers to improve their skills to access better opportunities. However, crowd work platforms like Amazon Mechanical Turk (AMT) generally do not support skill development (i.e., becoming faster and better at work). While researchers have started to tackle this problem, most solutions are dependent on experts or requesters willing to help. However, requesters generally lack the necessary knowledge, and experts are rare and expensive. To further facilitate crowd workers' skill growth, we present Crowd Coach, a system that enables workers to receive peer coaching while on the job. We conduct a field experiment and real world deployment to study Crowd Coach in the wild. Hundreds of workers used Crowd Coach in a variety of tasks, including writing, doing surveys, and labeling images. We find that Crowd Coach enhances workers' speed without sacrificing their work quality, especially in audio transcription tasks. We posit that peer coaching systems hold potential for better supporting crowd workers' skill development while on the job. We finish with design implications from our research.
Will Too Many Editors Spoil The Tag?
Authors: Choi Joohee , Tausczik Yla
Published: November 2018

Q&A websites compile useful knowledge through user-generated questions and responses. Many Q&As use collaborative tagging systems to improve search and discovery while distributing the work of categorizing and organization throughout the community. Although early work on collaborative tagging questioned whether consistent categorization schemes could emerge from large groups with little to no coordination, empirical studies have found surprising coherence among users' tags. We build on this research by testing whether coherence emerges in tag usage on Q&As, a more challenging context, focusing in particular on mismatches in the specificity of tags (basic level disagreement). We found that some users shifted toward more specific tag usage over time slightly increasing conflict, but that moderators were instrumental in helping to resolve some of this conflict. This study highlights the importance of learning and moderation in the development of coherence in collaborative tagging systems.
The Influence of Friends and Experts on Privacy Decision Making in IoT Scenarios
Authors: Emami Naeini Pardis , Degeling Martin , Bauer Lujo , Chow Richard , Cranor Lorrie Faith , Haghighat Mohammad Reza , Patterson Heather
Published: November 2018

As increasingly many Internet-of-Things (IoT) devices collect personal data, users face more privacy decisions. Personal privacy assistants can provide social cues and help users make informed decisions by presenting information about how others have decided in similar cases. To better understand which social cues are relevant and whose recommendations users are more likely to follow, we presented 1000 online participants with nine IoT data-collection scenarios. Some participants were told the percentage of experts or friends who allowed data collection in each scenario, while other participants were provided no social cue. At the conclusion of each scenario, participants were asked whether they would allow the described data collection. Our results help explain under what circumstances users are more or less likely to be swayed by the reported behavior of others in similar scenarios. For example, our results indicate that when friends denied data collection, our participants were more influenced than when friends allowed data collection. On the other hand, participants were more influenced by experts when they allowed data collection. We also observed that influence could get stronger or wear off when participants were exposed to a sequence of scenarios. For example, when experts and friends repeatedly allowed data collection in scenarios with clear risk or denied it in scenarios with clear benefits, participants were less likely to be influenced by them in subsequent scenarios.
GuessTheKarma
Authors: Glenski Maria , Stoddard Greg , Resnick Paul , Weninger Tim
Published: November 2018

Popularity systems, like Twitter retweets, Reddit upvotes, and Pinterest pins have the potential to guide people toward posts that others liked. That, however, creates a feedback loop that reduces their informativeness: items marked as more popular get more attention, so that additional upvotes and retweets may simply reflect the increased attention and not independent information about the fraction of people that like the items. How much information remains? For example, how confident can we be that more people prefer item A to item B if item A had hundreds of upvotes on Reddit and item B had only a few? We investigate using an Internet game called GuessTheKarma that collects independent preference judgments (N=20,674) for 400 pairs of images, approximately 50 per pair. Unlike the rating systems that dominate social media services, GuessTheKarma is devoid of social and ranking effects that influence ratings. Overall, Reddit scores were not very good predictors of the true population preferences for items as measured by GuessTheKarma: the image with higher score was preferred by a majority of independent raters only 68% of the time. However, when one image had a low score and the other was one of the highest scoring in its subreddit, the higher scoring image was preferred nearly 90% of the time by the majority of independent raters. Similarly, Imgur view counts for the images were poor predictors except when there were orders of magnitude differences between the pairs. We conclude that popularity systems marked by feedback loops may convey a strong signal about population preferences, but only when comparing items that received vastly different popularity scores.
Social Media as Social Transition Machinery
Authors: Haimson Oliver
Published: November 2018

Social media, and people's online self-presentations and social networks, add complexity to people's experiences managing changing identities during life transitions. I use gender transition as a case study to understand how people experience liminality on social media. I qualitatively analyzed data from transition blogs on Tumblr (n=240), a social media blogging site on which people document their gender transitions, and in-depth interviews with transgender bloggers (n=20). I apply ethnographer van Gennep's liminality framework to a social media context and contribute a new understanding of liminality by arguing that reconstructing one's online identity during life transitions is a rite of passage. During life transitions, people present multiple identities simultaneously on different social media sites that together comprise what I call social transition machinery. Social transition machinery describes the ways that, for people facing life transitions, multiple social media sites and networks o"en remain separate, yet work together to facilitate life transitions.
Sociocultural Practices that Make Microfinance Work
Authors: Halloluwa Thilina , Usoof Hakim , Vyas Dhaval
Published: November 2018

Microfinance is an inherently social process. Over the years, it has emerged as an essential means for providing financial services to the "underbanked" population in developing countries. This paper presents a qualitative study focused on understanding existing cooperative practices associated with microfinance in rural Sri Lanka. Through semi-structured interviews, group discussions and visits to microfinance centres, we found that microfinancing involves much more than financial transactions, rather it is strongly habituated in the sociocultural fabric of communities. Our findings show that three factors affect the cooperative process of microfinancing: trust and credibility, community support, and familial assistance. Using examples from the field, this paper discusses the importance of these factors in microfinance activities and contributes an elaborated account of cooperative practices that support microfinance processes. We also highlight how the local sociocultural structures and practices shape the way microfinance processes are being handled. We contribute towards an in-depth understanding of such practices that can be useful for microfinance institutions (MFIs) and technology designers. Consequently, we advocate for an intermediary path for technology interventions where technology and people work together rather than technology replacing people.
Who is Addressed in this Comment?
Authors: Häring Marlo , Loosen Wiebke , Maalej Walid
Published: November 2018

User comments have become an essential part of online journalism. However, newsrooms are often overwhelmed by the vast number of diverse comments, for which a manual analysis is barely feasible. Identifying meta-comments that address or mention newsrooms, individual journalists, or moderators and that may call for reactions is particularly critical. In this paper, we present an automated approach to identify and classify meta-comments. We compare comment classification based on manually extracted features with an end-to-end learning approach. We develop, optimize, and evaluate multiple classifiers on a comment dataset of the large German online newsroom SPIEGEL Online and the "One Million Posts" corpus of DER STANDARD, an Austrian newspaper. Both optimized classification approaches achieved encouraging
F
0.5
values between 76% and 91%. We report on the most significant classification features with the results of a qualitative analysis and discuss how our work contributes to making participation in online journalism more constructive.
Digitizing Monetary Ecologies
Authors: Hulikal Muralidhar Srihari , Bossen Claus , Mehra Apurv , O'Neill Jacki
Published: November 2018

This paper reports on the changes in the monetary ecology around loan payments by auto rickshaw drivers shortly after the introduction of a mobile app in Karnataka, India. A for-profit, social enterprise facilitates loans for purchasing auto rickshaws. The mobile app was designed and implemented to provide accurate, timely loan information for drivers, to support the collaborative work of loan collection payment, and streamline the workflows of the organization. In this paper, we report on the initial experiences with the app, and argue that its introduction led to a tighter coupling of the actors involved and moved control to the back office, which especially impacted the pre- and at-transaction interactions of the monetary ecology. The paper reflects on how these changes impact adoption and use of the app and suggests a number of changes to the design which might address the observed problematics.
Debiasing Desire
Authors: Hutson Jevan A. , Taft Jessie G. , Barocas Solon , Levy Karen
Published: November 2018

Designing technical systems to be resistant to bias and discrimination represents vital new terrain for researchers, policymakers, and the anti-discrimination project more broadly. We consider bias and discrimination in the context of popular online dating and hookup platforms in the United States, which we call intimate platforms. Drawing on work in social-justice-oriented and Queer HCI, we review design features of popular intimate platforms and their potential role in exacerbating or mitigating interpersonal bias. We argue that focusing on platform design can reveal opportunities to reshape troubling patterns of intimate contact without overriding users' decisional autonomy. We identify and address the difficult ethical questions that nevertheless come along with such intervention, while urging the social computing community to engage more deeply with issues of bias, discrimination, and exclusion in the study and design of intimate platforms.
Bridging Disconnected Knowledges for Community Health
Authors: Ismail Azra , Karusala Naveena , Kumar Neha
Published: November 2018

We conducted a field study of Mohalla Clinics in Delhi (India), drawing on Haraway's work to highlight the importance of considering disparate, partial perspectives in the ecologies of such clinics. We emphasized that inadequate attention given to patients' and health workers' perspectives, and the low preparedness of the doctors at the clinics, resulted in the clinics being unable to address the needs of target patient groups. We concluded by contributing to ongoing, important conversations in the fields of ICTD, CSCW, and HCI towards redesigning healthcare interventions, revisiting patient empowerment, and redefining the role of ASHAs as infomediaries.
'The Perfect One'
Authors: Jiang Jialun "Aaron" , Fiesler Casey , Brubaker Jed R.
Published: November 2018

Animated GIFs are increasingly popular in text-based communication. Finding the perfect GIF can make conversations funny, interesting, and engaging, but GIFs also introduce potentials for miscommunication. Through 24 in-depth qualitative interviews, this empirical, exploratory study examines the nuances of communication practices with animated GIFs to better understand why and how GIFs can send unintentional messages. We find participants leverage contexts like source material and interpersonal relationship to find the perfect GIFs for different communication scenarios, while these contexts are also the primary reason for miscommunication and some technical usability issues. This paper concludes with a discussion of the important role that different types of context play in the use and interpretations of GIFs, and argues that nonverbal communication tools should account for complex contexts and common ground that communication media rely on.
Tending Unmarked Graves
Authors: Jiang Jialun "Aaron" , Brubaker Jed R.
Published: November 2018

User-generated content is central to social computing scholarship. However, researchers and practitioners often presume that these users are alive. Failing to account for mortality is problematic in social media where an increasing number of profiles represent those who have died. Identifying mortality can empower designers to better manage content and support the bereaved, as well as promote high-quality data science. Based on a computational linguistic analysis of post-mortem social media profiles and content, we report on classifiers developed to detect mortality and show that mortality can be determined after the first few occurrences of post-mortem content. Applying our classifiers to content from two other platforms also provided good results. Finally, we discuss trade-offs between models that emphasize pre- vs. post-mortem precision in this sensitive context. These results mark a first step toward identifying mortality at scale, and show how designers and scientists can attend to mortality in their work.
Digestif
Authors: Jun Eunice , Jo Blue A. , Oliveira Nigini , Reinecke Katharina
Published: November 2018

Online experiments allow researchers to collect data from large, demographically diverse global populations. Unlike in-lab studies, however, online experiments often fail to inform participants about the research to which they contribute. This paper is the first to investigate barriers that prevent researchers from providing such science communication in online experiments. We found that the main obstacles preventing researchers from including such information are assumptions about participant disinterest, limited time, concerns about losing anonymity, and concerns about experimental bias. Researchers also noted the dearth of tools to help them close the information loop with their study participants. Based on these findings, we formulated design requirements and implemented Digestif, a new web-based tool that supports researchers in providing their participants with science communication pages. Our evaluation shows that Digestif's scaffolding, examples, and nudges to focus on participants make researchers more aware of their participants' curiosity about research and more likely to disclose pertinent research information.
Reciprocity and Donation
Authors: Kocielnik Rafal , Keyes Os , Morgan Jonathan T. , Taraborelli Dario , McDonald David W. , Hsieh Gary
Published: November 2018

Donation-based support for open, peer production projects such as Wikipedia is an important mechanism for preserving their integrity and independence. For this reason understanding donation behavior and incentives is crucial in this context. In this work, using a dataset of aggregated donation information from Wikimedia's 2015 fund-raising campaign, representing nearly 1 million pages from English and French language versions of Wikipedia, we explore the relationship between the properties of contents of a page and the number of donations on this page. Our results suggest the existence of a reciprocity mechanism, meaning that articles that provide more utility value attract a higher rate of donation. We discuss these and other findings focusing on the impact they may have on the design of banner-based fundraising campaigns. Our findings shed more light on the mechanisms that lead people to donate to Wikipedia and the relation between properties of contents and donations.
"What do you recommend a complete beginner like me to practice?"
Authors: Kou Yubo , Gray Colin M.
Published: November 2018

CSCW scholarship has previously addressed how professionals use digital technologies for learning and communication, but limited attention has been paid to professional self-disclosure on social media. Acts of self-disclosure-intentionally revealing personal information to others-are often considered beneficial for communication and formation of relationships, and describing the role of disclosure in professional communication is important to advance CSCW research that focuses on occupations or organizational settings. In this paper, we present a mixed-methods study of professional self-disclosure in an online community focused on user experience design (UX), documenting how acts of self-disclosure may support professional development. We found that self-disclosure was frequently used as an effective rhetorical and content-focused strategy to provoke discussions and request assistance with the goal of developing or maintaining professional competence. Through the identification of these self-disclosure strategies, we discuss professional self-disclosure in relation to professional identity development in online communities.
How Much is 'Too Much'?
Authors: Lanette Simone , Chua Phoebe K. , Hayes Gillian , Mazmanian Melissa
Published: November 2018

In a mixed methods study of parents and teens (n=200), 87% (n=174) of participants used language consistent with smartphone addiction narratives when asked about their smartphone feelings and use. Mental health researchers and clinicians do not consistently agree about whether smartphone addiction exists nor what it would look like if it does. Our goal in this study was to explore the patterns of responses that people invoked when talking about the role of smartphones in their lives and the lives of those around them. Responses suggested that both parents and teens are aware of and potentially influenced by a narrative that smartphones are addictive and can lead to negative, though largely undefined, consequences. We examine potential origins of this narrative, including media coverage, and examine the critical need for a deeper examination in the CSCW community of how this narrative could be influencing well-being, sense of self, and sensemaking around smartphone use.
Alexa, Are You Listening?
Authors: Lau Josephine , Zimmerman Benjamin , Schaub Florian
Published: November 2018

Smart speakers with voice assistants, like Amazon Echo and Google Home, provide benefits and convenience but also raise privacy concerns due to their continuously listening microphones. We studied people's reasons for and against adopting smart speakers, their privacy perceptions and concerns, and their privacy-seeking behaviors around smart speakers. We conducted a diary study and interviews with seventeen smart speaker users and interviews with seventeen non-users. We found that many non-users did not see the utility of smart speakers or did not trust speaker companies. In contrast, users express few privacy concerns, but their rationalizations indicate an incomplete understanding of privacy risks, a complicated trust relationship with speaker companies, and a reliance on the socio-technical context in which smart speakers reside. Users trade privacy for convenience with different levels of deliberation and privacy resignation. Privacy tensions arise between primary, secondary, and incidental users of smart speakers. Finally, current smart speaker privacy controls are rarely used, as they are not well-aligned with users' needs. Our findings can inform future smart speaker designs; in particular we recommend better integrating privacy controls into smart speaker interaction.
Negotiating Relation Work with Telehealth Home Care Companionship Technologies that Support Aging in Place
Authors: Lazar Amanda , Thompson Hilaire J. , Lin Shih-Yin , Demiris George
Published: November 2018

In response to a perceived caregiver shortage and need to support aging in place, telehealth home care systems are being developed to provide remote care and monitoring to older people. Though research has examined the experiences of teleoperators delivering care through these systems, we know less about the experiences of older adults receiving this care. We report findings from a three-month study of a tablet-based telehealth home care system that provides support for aging in place. We find that there is a mismatch between the designer's conception of how care should be delivered and the ways that participants were interested in using the system. This mismatch exists in four areas: participants' interest in getting to know the human teleoperators and rejecting the virtual avatar, interrogating the interface to figure out the inner workings of the platform, pushing for a more symmetrical relationship, and negotiating the relation work that they were willing to perform in the "sacred space" of their homes. We draw on the concept of heteromation to understand the political dimensions of telehealth aging in place technologies. We also provide implications and future directions for technologies requiring relation work as well as the design of avatar-based remote companionship.
Opinion Conflicts
Authors: Maity Suman Kalyan , Chakraborty Aishik , Goyal Pawan , Mukherjee Animesh
Published: November 2018

In Twitter, there is a rising trend in abusive behavior which often leads to incivility. This trend is affecting users mentally and as a result they tend to leave Twitter and other such social networking sites thus depleting the active user base. In this paper, we study factors associated with incivility. We observe that the act of incivility is highly correlated with the opinion differences between the account holder (i.e., the user writing the incivil tweet) and the target (i.e., the user for whom the incivil tweet is meant for or targeted), toward a named entity. We introduce a character level CNN model and incorporate the entity-specific sentiment information for efficient incivility detection which significantly outperforms multiple baseline methods achieving an impressive accuracy of 93.3% (4.9% improvement over the best baseline). In a post-hoc analysis, we also study the behavioral aspects of the targets and account holders and try to understand the reasons behind the incivility incidents. Interestingly, we observe that there are strong signals of repetitions in incivil behavior. In particular, we find that there are a significant fraction of account holders who act as repeat offenders - attacking the targets even more than 10 times. Similarly, there are also targets who get targeted multiple times. In general, the targets are found to have higher reputation scores than the account holders.
Endorsements on Social Media
Authors: Mathur Arunesh , Narayanan Arvind , Chetty Marshini
Published: November 2018

Online advertisements that masquerade as non-advertising content pose numerous risks to users. Such hidden advertisements appear on social media platforms when content creators or "influencers" endorse products and brands in their content. While the Federal Trade Commission (FTC) requires content creators to disclose their endorsements in order to prevent deception and harm to users, we do not know whether and how content creators comply with the FTC's guidelines. In this paper, we studied disclosures within affiliate marketing, an endorsement-based advertising strategy used by social media content creators. We examined whether content creators follow the FTC's disclosure guidelines, how they word the disclosures, and whether these disclosures help users identify affiliate marketing content as advertisements. To do so, we first measured the prevalence of and identified the types of disclosures in over 500,000 YouTube videos and 2.1 million Pinterest pins. We then conducted a user study with 1,791 participants to test the efficacy of these disclosures. Our findings reveal that only about 10% of affiliate marketing content on both platforms contains any disclosures at all. Further, users fail to understand shorter, non-explanatory disclosures. Based on our findings, we make various design and policy suggestions to help improve advertising disclosure practices on social media platforms.
Domino
Authors: Neumayr Thomas , Jetter Hans-Christian , Augstein Mirjam , Friedl Judith , Luger Thomas
Published: November 2018

We present Domino, a descriptive framework for hybrid collaboration and hybrid coupling styles in partially distributed teams. Domino enables researchers to describe, analyze, and understand real-world hybrid collaboration practices, i.e., collaborative practices that involve simultaneous co-located and remote collaboration with phases of both synchronous and asynchronous work that spans multiple groupware applications and devices. It also helps to categorize collaborative activities based on yet undocumented hybrid coupling styles between the members of multiple partially distributed or co-located subgroups. Our Domino framework was derived from initial observations of real-world practice and refined by the detailed analysis of participants' behavior and working styles during a simulation of a complex hybrid collaboration task with six partially distributed teams of four users in our lab. The resulting framework allows researchers to view collaboration through a new analytical lens, use new analytical tools, and also derive implications for the design of collaborative tools.
People Tend to Wind Down, Not Up, When They Browse Social Media
Authors: Panger Galen
Published: November 2018

Researchers have focused intensively on the emotional effects of browsing social media, with many emphasizing possible negative effects and others suggesting the positive emotions in status updates are contagious. Despite this focus, however, very few studies have investigated the actual emotional experience of browsing social media in the moment, and none with more than a few emotions, making it difficult to understand the effects research should endeavor to explain. To address this gap, I use experience sampling with diverse samples of Facebook (N = 362) and Twitter (N = 416) users, assessing the browsing experience across a wide range of emotions. Surprisingly, results provide little evidence of robust positive or negative effects, suggesting instead that the primary effect of browsing social media is a lessening of arousal. That is, contrary to stereotype, people tend to wind down - feel more relaxed, sleepy, bored and so on - not wind up.
Who Models the World?
Authors: Piscopo Alessandro , Simperl Elena
Published: November 2018

Wikidata is a collaborative knowledge graph which is central to many academic and industry IT projects. Its users are responsible for maintaining the schema that organises this knowledge into classes, properties, and attributes, which together form the Wikidata 'ontology'. In this paper, we study the relationship between different Wikidata user roles and the quality of the Wikidata ontology. To do so we first propose a framework to evaluate the ontology as it evolves. We then cluster editing activities to identify user roles in monthly time frames. Finally, we explore how each role impacts the ontology. Our analysis shows that the Wikidata ontology has uneven breadth and depth. We identified two user roles: contributors and leaders. The second category is positively associated to ontology depth, with no significant effect on other features. Further work should investigate other dimensions to define user profiles and their influence on the knowledge graph.
The Spirit of the City
Authors: Redi Miriam , Aiello Luca Maria , Schifanella Rossano , Quercia Daniele
Published: November 2018

Place ambiance has a huge influence over how we perceive places. Despite its importance, ambiance has been crucially overlooked by urban planners and scientists alike, not least because it is difficult to record and analyze at scale. We explored the possibility of using social media data to reliably map the ambiance of neighborhoods in the entire city of London. To this end, we collected geo-referenced picture tags from Flickr and matched those tags with the words in a newly created ambiance dictionary. In so doing, we made four main contributions: i) map the ambiance of London neighborhoods; ii) ascertain that such a mapping meets residents' expectations, which are derived from a survey we conducted; iii) show that computer vision techniques upon geo-referenced pictures are of predictive power for neighborhood ambiance; and iv) explain each prediction of a neighborhood's ambiance by identifying the picture that best reflects the meaning of that ambiance (e.g., artsy) in that neighborhood (e.g., South Kensington---the richest and most traditional neighborhood---and Shoreditch---among the most progressive and hipster neighborhoods in the city---are both 'artsy' but in very different ways). The combination of the predictive power of mapping ambiance from images and the ability to explain those predictions makes it possible to discover hidden gems across the city at an unprecedented scale.
Socio-spatial Self-organizing Maps
Authors: Relia Kunal , Akbari Mohammad , Duncan Dustin , Chunara Rumi
Published: November 2018

Social media offers a unique window into attitudes like racism and homophobia, exposure to which are important, hard to measure and understudied social determinants of health. However, individual geo-located observations from social media are noisy and geographically inconsistent. Existing areas by which exposures are measured, like Zip codes, average over irrelevant administratively-defined boundaries. Hence, in order to enable studies of online social environmental measures like attitudes on social media and their possible relationship to health outcomes, first there is a need for a method to define the collective, underlying degree of social media attitudes by region. To address this, we create the Socio-spatial-Self organizing map, "SS-SOM" pipeline to best identify regions by their latent social attitude from Twitter posts. SS-SOMs use neural embedding for text-classification, and augment traditional SOMs to generate a controlled number of non-overlapping, topologically-constrained and topically-similar clusters. We find that not only are SS-SOMs robust to missing data, the exposure of a cohort of men who are susceptible to multiple racism and homophobia-linked health outcomes, changes by up to 42% using SS-SOM measures as compared to using Zip code-based measures.
Auditing Partisan Audience Bias within Google Search
Authors: Robertson Ronald E. , Jiang Shan , Joseph Kenneth , Friedland Lisa , Lazer David , Wilson Christo
Published: November 2018

There is a growing consensus that online platforms have a systematic influence on the democratic process. However, research beyond social media is limited. In this paper, we report the results of a mixed-methods algorithm audit of partisan audience bias and personalization within Google Search. Following Donald Trump's inauguration, we recruited 187 participants to complete a survey and install a browser extension that enabled us to collect Search Engine Results Pages (SERPs) from their computers. To quantify partisan audience bias, we developed a domain-level score by leveraging the sharing propensities of registered voters on a large Twitter panel. We found little evidence for the "filter bubble'' hypothesis. Instead, we found that results positioned toward the bottom of Google SERPs were more left-leaning than results positioned toward the top, and that the direction and magnitude of overall lean varied by search query, component type (e.g. "answer boxes"), and other factors. Utilizing rank-weighted metrics that we adapted from prior work, we also found that Google's rankings shifted the average lean of SERPs to the right of their unweighted average.
Aiding Collaborative Reuse of Computational Notebooks with Annotated Cell Folding
Authors: Rule Adam , Drosos Ian , Tabard Aurélien , Hollan James D.
Published: November 2018

Computational notebooks aim to support collaborative data analysis by combining code, visualizations, and text in a single easily shared document. Yet, as notebooks evolve and grow they often become difficult to navigate or understand, discouraging sharing and reuse. We present the design and evaluation of a Jupyter Notebook extension providing facilities for annotated cell folding. Through a lab study and multi-week deployment we find cell folding aids notebook navigation and comprehension, not only by the original author, but also by collaborators viewing the notebook in a meeting or revising it on their own. However, in some cases cell folding encouraged collaborators to overlook folded sections or spend longer reviewing a notebook before editing it. These findings extend our understanding of code folding's trade-offs to a new medium and demonstrate its benefits for everyday collaboration. We conclude by discussing how dynamic reorganization can support sharing and reuse of computational notebooks.
Older Adults and Crowdsourcing
Authors: Skorupska Kinga , Nunez Manuel , Kopec Wieslaw , Nielek Radoslaw
Published: November 2018

In this paper we describe the insights from an exploratory qualitative pilot study testing the feasibility of a solution that would encourage older adults to participate in online crowdsourcing tasks in a non-computer scenario. Therefore, we developed an Android TV application using Amara API to retrieve subtitles for TEDx talks which allows the participants to detect and categorize errors to support the quality of the translation and transcription processes. It relies on the older adults' innate skills as long-time native language users and the motivating factors of this socially and personally beneficial task. The study allowed us to verify the underlying concept of using Smart TVs as interfaces for crowdsourcing, as well as possible barriers, including the interface, configuration issues, topics and the process itself. We have also assessed the older adults' interaction and engagement with this TV-enabled online crowdsourcing task and we are convinced that the design of our setup addresses some key barriers to crowdsourcing by older adults. It also validates avenues for further research in this area focused on such considerations as autonomy and freedom of choice, familiarity, physical and cognitive comfort as well as building confidence and the edutainment value.
Learning
from
and
with
Menstrupedia
Authors: Tuli Anupriya , Chopra Shaan , Kumar Neha , Singh Pushpendra
Published: November 2018

Menstruation has long remained a conversational taboo across India, resulting in inadequate dissemination of menstrual health education (MHE). Menstrupedia, a digital platform designed for an Indian audience, aims to bridge this information gap to impart MHE via its website and comic. We contribute a study of Menstrupedia---the information exchange on its website, the education it aims to provide, and the perceptions of its users. Using a combination of qualitative research methods, and engaging a feminist Human-Computer Interaction (HCI) lens, we critically analyze Menstrupedia's affordances and shortcomings. We also make recommendations for the design of technology-based dissemination of MHE, as well as additional sensitive and taboo topics.
Accessibility in Action
Authors: Wang Emily Q. , Piper Anne Marie
Published: November 2018

Although accessibility in academic and professional workplaces is a well-known issue, understanding how teams with different abilities communicate and coordinate in technology-rich workspaces is less well understood. When hearing people collaborate around computers, they rely on the ability to simultaneously see and hear as they start a shared document, talk to each other while editing, and gesture towards the screen. This interaction norm breaks down for teams of people with different sensory abilities, such as Deaf and hearing collaborators, who rely on visual communication. Through interviews and observations, we analyze how Deaf-hearing teams collaborate on a variety of naturalistic tasks. Our findings reveal that Deaf-hearing teams create accessibility through their moment-to-moment co-located interaction and emerging team practices over time. We conclude with a discussion of how studying co-located Deaf-hearing interaction extends our understanding of accessibility in mixed-ability teams and provides new insights for groupware systems.
Participating Through Data
Authors: Wolf Christine T. , Ringland Kathryn E. , Gao Isley , Dourish Paul
Published: November 2018

Engagements with social media today frequently involve the use of multiple platforms, which often exchange personal data about users. We explore individuals' experiences with the flow of personal data across platforms through interviews about dating apps, often requiring integration with a Facebook account. Inductive analysis revealed complex and, at times, conflicted ideas over what appropriate behaviors around personal data should look like in multiplatform engagements-central to these tensions were the multiple relationships that must be managed through participation in these ecosystems. For example, individuals talked of resignation in relation to specific platforms and the 'cost" of using free services (people:platform), a lack of clarity and agency in defining what personal data might be shared between platforms (people:platform:platform), and, of course, the role of personal data in their efforts to establish and maintain relationships with other users in these 'social discovery" ecosystems (people:people). We explore how these attitudes can be understood as morally charged, drawing attention to the ways in which personal data flows can enact expectations and obligations between various sociotechnical actors in personal data ecosystems and how these compound relationships reveal the complexity and texture of multiplatform participation.
Investigating Separation of Territories and Activity Roles in Children's Collaboration around Tabletops
Authors: Woodward Julia , Esmaeili Shaghayegh , Jain Ayushi , Bell John , Ruiz Jaime , Anthony Lisa
Published: November 2018

Prior work has shown that children exhibit negative collaborative behaviors, such as blocking others' access to objects, when collaborating on interactive tabletop computers. We implemented previous design recommendations, namely separate physical territories and activity roles, which had been recommended to decrease these negative collaborative behaviors. We developed a multi-touch "I-Spy" picture searching application with separate territory partitions and activity roles. We conducted a deep qualitative analysis of how six pairs of children, ages 6 to 10, interacted with the application. Our analysis revealed that the collaboration styles differed for each pair, both in regards to the interaction with the task and with each other. Several pairs exhibited negative physical and verbal collaborative behaviors, such as nudging each other out of the way. Based on our analysis, we suggest that it is important for a collaborative task to offer equal opportunities for interaction, but it may not be necessary to strive for complete equity of collaboration. We examine the applicability of prior design guidelines and suggest open questions for future research to inform the design of tabletop applications to support collaboration for children.