bluuebunny/crossref_metadata_2025 huggingface dataset:
Is this nice for mice?
Authors: Williams David
Published: November 2018

THIS series gives readers the opportunity to consider and contribute to discussion of some of the ethical dilemmas that can arise in veterinary practice. Each month, a case scenario is presented, followed by discussion of some of the issues involved.

In addition, a possible way forward is suggested; however, there is rarely a cut‐and‐dried answer in such cases, and readers may wish to suggest an alternative approach. This month's dilemma, ‘Is this nice for mice?’, was submitted and is discussed by David Williams. Readers with comments to contribute are invited to send them as soon as possible, so that they can be considered for publication in the next issue.

The series is being coordinated by Dr Steven McCulloch, acting director of the Centre for Animal Welfare, University of Winchester. It aims to provide a framework that will help practising veterinarians find solutions when facing similar dilemmas.
Significance of biglycan and osteopontin as non-invasive markers of liver fibrosis in patients with chronic hepatitis B virus and chronic hepatitis C virus
Authors: Sobhy Ali , Mohammed Fakhry M. , Haitham A Azeem , Ashmawy Ahmed M , Omar Khalifa Hamed
Published: November 2018

Several studies were performed to evaluate the degree of liver fibrosis by non-invasive markers. We aimed to assess the diagnostic value of both biglycan (BGN) and osteopontin (OPN) as non-invasive markers of hepatic fibrosis in patients with chronic hepatitis B (CHB) and chronic hepatitis C (CHC). This study was performed on 100 patients with CHB virus, 100 patients with CHC virus and 100 normal controls. All participants were subjected to the following laboratory tests: hemoglobin, platelet, alanine aminotransferase, aspartate aminotransferase, albumin, international normalized ratio, HBs Ag, hepatitis C virus (HCV) antibody, hepatitis B virus DNA, HCV RNA, liver biopsy, BGN and OPN. We found that BGN level was significantly increased in the CHB group compared with the controls (p<0.001), but the level was not different between the CHC group and the controls (p<0.96). OPN was increased in both the CHB and CHC groups compared with the controls (p<0.001). Positive correlation was found between fibrosis stages and BGN level of the CHB group (r=0.64; p<0.001) and between fibrosis stages and OPN level of the CHB (r=0.63; p<0.001) and CHC (r=0.59; p<0.03) groups. The area under the curve (AUC), sensitivity and specificity of BGN were 1.0, 100% and 100% in predicting fibrosis in patients with CHB, and 0.50, 26% and 78% in predicting fibrosis in patients with CHC. OPN had an AUC of 0.997, sensitivity of 96% and specificity of 100% in predicting fibrosis in patients with CHB, and 0.974, 96.5% and 100% in predicting fibrosis in patients with CHC. In conclusion, BGN and OPN could be considered non-invasive markers for liver fibrosis assessment.
Geochemistry of Late Ordovician dalmanelloid brachiopods from Laurentia: testing the effects of paleolatitudinal gradient
Authors: Azmy Karem , Jin Jisuo
Published: November 2018

Dalmanelloid brachiopod shells were collected from the Upper Ordovician Lexington Formation (lower Katian) of Kentucky, Sheguindah Shale (middle Katian) on Manitoulin Island, Ontario, and the Stony Mountain Formation (upper Katian) in the Winnipeg area, Manitoba. They were investigated to test the hypothesis of paleo-latitudinal zonation of the shelly benthos. A multi-technique approach was applied to evaluate the petrographic and geochemical (isotopic and elemental) preservation of the secondary layer of shells. Preliminary conventional microscopy, cathodoluminescence (CL), and scanning electron microscopy (SEM) confirmed the retention of primary shell ultrastructure (prismatic low-Mg calcite). The geochemical diagenesis proxies (e.g., Sr, Mn, Fe, and ΣREE) show insignificant correlations with the δ18O and δ13C values, thus supporting the preservation of at least near-primary geochemical compositions. Among the three lots of shells, the mean δ18O value is the highest in those from the Lexington Formation (–4.5‰ ± 0.3‰ VPDB), lowest from the Stony Mountain Formation (–6.8‰ ± 0.4‰ VPDB), and intermediate from the Sheguindah Shale (–6.0‰ ± 0.8‰ VPDB). The relative gradient in δ18O increase is in agreement with the paleo-latitudinal gradient, with Kentucky in subtropical, southern Ontario in mid-tropical, and southern Manitoba in subequatorial latitudes. The Lexington Formation shells also have the highest mean δ13C value (0.8‰ ± 0.2‰ VPDB) and relatively high P contents (170 ± 27 ppm), suggesting higher organic productivity, which is consistent with previous interpretation of frequent upwelling of nutrient-rich cool waters along the southeastern margin of Laurentia during the Katian. The Lexington shells also have a lower mean Th/U (0.6 ± 0.6), which is consistent with blooming organic productivity that likely led to more consumption of oxygen in the water column.
Age matters: Submersion period shapes community composition of lake biofilms under glyphosate stress
Authors: Khadra Melissa , Planas Dolors , Girard Catherine , Amyot Marc
Published: November 2018

The phosphonate herbicide glyphosate, which is the active ingredient in the commercial formulation Roundup®, is currently the most globally used herbicide. In aquatic ecosystems, periphytic biofilms, or periphyton, are at the base of food webs and are often the first communities to be in direct contact with runoff. Microcosm experiments were conducted to assess the effects of a pulse exposure of glyphosate on community composition and chlorophyll a concentrations of lake biofilms at different colonization stages (2 months, 1 year, and 20 years). This is the first study that uses such contrasting submersion periods. Biofilms were exposed to either environmental levels of pure analytical grade glyphosate (6 μg/L, 65 μg/L, and 600 μg/L) or to corresponding phosphorus concentrations. Community composition was determined by deep sequencing of the 18S and 16S rRNA genes to target eukaryotes and cyanobacteria, respectively. The results showed that submersion period was the only significant contributor to community structure. However, at the taxon level, the potentially toxic genus Anabaena was found to increase in relative abundance. We also observed that glyphosate releases phosphorus into the surrounding water, but not in a bioavailable form. The results of this study indicate that environmental concentrations of glyphosate do not seem to impact the community composition or metabolism of lake biofilms under pulse event conditions.
Contextual Determinants of Employee Entrepreneurial Behavior in Support of Corporate Entrepreneurship: A Systematic Review and Research Agenda
Authors: Mustafa Michael , Gavin Fiona , Hughes Mathew
Published: November 2018

The individual entrepreneurial behavior of employees represents one of the primary antecedents of Corporate Entrepreneurship. The complex nature of ‘employee entrepreneurial behavior’ suggests that a myriad of contextual influences act on the emergence of such behavior. It is imperative that theorists and practitioners alike understand both the subtle and sophisticated ways in which context influences employee entrepreneurial behavior. To address these issues and encourage future work, this study performs a systematic literature review to provide an overview of the field and examines the influence of the job/role, organizational/work and external contexts on employee entrepreneurial behavior. Findings suggest that employee entrepreneurial behavior is an emergent research field and that its behaviors can manifest themselves in different ways compared to firm-level entrepreneurial behaviors. We also show the sophisticated manner in which different types of context influence employee entrepreneurial behavior.
HIP MOTION ANALYSIS USING PARAMETRIC MATHEMATICAL MODELING IN MIDDLE AGED TO ELDERLY ADULTS DURING WALKING
Authors: ZHANG LIXUN , SONG DA , WANG BINGJUN , XUE FENG
Published: November 2018

Human gait is influenced by changes in joints of the pelvis, hips, knees and ankles, which demonstrate three degrees of freedom. Thus, this study presents a mathematical model for the establishment of the hip rotation trajectory using measured data. We used multibody dynamics simulation software (LifeMOD) to establish a model of the human lower limb, whereby the three dimensional trajectory of the hip joint could be analyzed. We used advanced equipment to measure the trajectories of the internal rotation and external rotation of the hip joint in middle aged to elderly adults during walking. Curve fitting was used to obtain the average internal rotation and external rotation of the hip joint, and relationships between the amplitude, period, initial movement phase, subject height and walking speed were assessed. The observations from this study suggest that mathematical modeling of internal rotation and external rotation of hip joint can be performed using this approach. This modeling technique can be used to track the trajectory planning of rehabilitation robots and the external skeletons leading to improved human–computer interactions, and evaluation of response to rehabilitation.
CONTINUOUS SENSORY ELECTRICAL STIMULATION FOR THE SUPPRESSION OF PARKINSONIAN REST TREMOR
Authors: HEO JAE-HOON , JEON HYEONG-MIN , CHOI EUI-BUM , KWON DO-YOUNG , EOM GWANG-MOON
Published: November 2018

This paper aims to investigate the effect of continuous sensory electrical stimulation (SES) on the suppression of a Parkinsonian rest tremor. Fourteen patients with Parkinson’s disease participated in this study. Three wrist muscles were electrically stimulated on sensory level under motor threshold. Intensity of stimulation was determined for each muscle of each patient as the maximum tolerable current amplitude that does not induce muscle contraction. Tri-axial gyro sensors were attached to three upper limb segments. The angular velocity of each segment was measured for each of the three sessions, i.e., PRE-, ON- and POST- stimulations. Outcome measures were the tremor amplitude and main frequency of each axis in the power spectrum. Decrease in tremor amplitude was significant at ON and POST sessions in finger and at POST session in hand and forearm. Decrease in main frequency was significant mainly at ON session. About one-third of patients showed reduction in tremor power at ON-stimulation and at POST-stimulation. Subjects with suppression of tremor showed greater initial tremor amplitude than those without suppression. Continuous SES suppressed the Parkinsonian rest tremor. The results suggest that the properties of tremor-generating loop may be altered by continuous SES and the effect lasts temporarily.
Experiences with SIGCSE
Authors: Young Frank H.
Published: November 2018

Excerpts from the First-Timers Luncheon talk given at SIGCSE 2015
TPM
Authors: Wang Weiqing , Yin Hongzhi , Du Xingzhong , Nguyen Quoc Viet Hung , Zhou Xiaofang
Published: November 2018

With the rapid development of location-based social networks (LBSNs), spatial item recommendation has become an important way of helping users discover interesting locations to increase their engagement with location-based services. The availability of spatial, temporal, and social information in LBSNs offers an unprecedented opportunity to enhance the spatial item recommendation. Many previous works studied spatial and social influences on spatial item recommendation in LBSNs. Due to the strong correlations between a user’s check-in time and the corresponding check-in location, which include the sequential influence and temporal cyclic effect, it is essential for spatial item recommender system to exploit the temporal effect to improve the recommendation accuracy. Leveraging temporal information in spatial item recommendation is, however, very challenging, considering (1) when integrating sequential influences, users’ check-in data in LBSNs has a low sampling rate in both space and time, which renders existing location prediction techniques on GPS trajectories ineffective, and the prediction space is extremely large, with millions of distinct locations as the next prediction target, which impedes the application of classical Markov chain models; (2) there are various temporal cyclic patterns (i.e., daily, weekly, and monthly) in LBSNs, but existing work is limited to one specific pattern; and (3) there is no existing framework that unifies users’ personal interests, temporal cyclic patterns, and the sequential influence of recently visited locations in a principled manner.

In light of the above challenges, we propose a Temporal Personalized Model (
TPM
), which introduces a novel latent variable
topic-region
to model and fuse sequential influence, cyclic patterns with personal interests in the latent and exponential space. The advantages of modeling the temporal effect at the topic-region level include a significantly reduced prediction space, an effective alleviation of data sparsity, and a direct expression of the semantic meaning of users’ spatial activities. Moreover, we introduce two methods to model the effect of various cyclic patterns. The first method is a time indexing scheme that encodes the effect of various cyclic patterns into a binary code. However, the indexing scheme faces the data sparsity problem in each time slice. To deal with this data sparsity problem, the second method slices the time according to each cyclic pattern separately and explores these patterns in a joint additive model.

Furthermore, we design an asymmetric Locality Sensitive Hashing (ALSH) technique to speed up the online top-
k
recommendation process by extending the traditional LSH. We evaluate the performance of TPM on two real datasets and one large-scale synthetic dataset. The performance of TPM in recommending cold-start items is also evaluated. The results demonstrate a significant improvement in TPM’s ability to recommend spatial items, in terms of both effectiveness and efficiency, compared with the state-of-the-art methods.
A Cross-Domain Recommendation Mechanism for Cold-Start Users Based on Partial Least Squares Regression
Authors: Li Cheng-Te , Hsu Chia-Tai , Shan Man-Kwan
Published: November 2018

Recommender systems are common in e-commerce platforms in recent years. Recommender systems are able to help users find preferential items among a large amount of products so that users’ time is saved and sellers’ profits are increased. Cross-domain recommender systems aim to recommend items based on users’ different tastes across domains. While recommender systems usually suffer from the user cold-start problem that leads to unsatisfying recommendation performance, cross-domain recommendation can remedy such a problem. This article proposes a novel cross-domain recommendation model based on regression analysis, partial least squares regression (PLSR). The proposed recommendation models, PLSR-CrossRec and PLSR-Latent, are able to purely use source-domain ratings to predict the ratings for cold-start users who never rated items in the target domains. Experiments conducted on the Epinions dataset with ten various domains’ rating records demonstrate that PLSR-Latent can outperform several matrix factorization-based competing methods under a variety of cross-domain settings. The time efficiency of PLSR-Latent is also satisfactory.
Editors' Message
Authors: Karahalios Karrie , Monroy-Hernández Andrés , Lampinen Airi , Fitzpatrick Geraldine
Published: November 2018

It is our great pleasure to welcome you to this issue of the Proceedings of the ACM on Human Computer Interaction, the second to focus on the contributions from the research community Computer-Supported Cooperative Work and Social Computing (CSCW).

This journal model allows for rapid publication of papers shortly after acceptance as well as enabling automatic indexing services, such as Institute for Scientific Information (ISI) indexing. The aim is to increase the visibility of the work of authors in this community, and allow for better comparability with fields outside of Computer Science.

This issue contains papers accepted over two iterations of the review process. The call for papers for this second issue, with an initial deadline in Spring 2018, attracted 722 submissions, from all around the world. After the first round of reviewing, 326 (45,2%) papers were invited to the Revise and Resubmit phase. The program committee worked hard over August 2018 to arrive at final decisions, with an online editorial committee meeting held to allow for collective deliberation. In the end, 184 papers (25,5%) were accepted.

For some of those papers, authors received further shepherding and guidance by a senior committee member. This shows the commitment of the CSCW community to not only ensure high quality contributions, but also to educate and enable authors to write and present their best work for this community. This issue exists because of the dedicated volunteer effort of 132 senior editorial committee members who served as Associate Chairs (ACs), and 837 external expert reviewers to ensure high quality and insightful reviews for all papers in both rounds.
Quotidian Report
Authors: Alvarado Garcia Adriana , Le Dantec Christopher A.
Published: November 2018

We examine the local data practices of citizens in Mexico who use Facebook sites as a platform to report crimes and share safety-related information. We conducted 14 interviews with a variety of participants who collaborate as administrators and contributors of these online communities. The communities we examined have two central components: the citizens who crowd-source data about instances of crime in different neighborhoods in and around Mexico City, and the administrators of the Facebook sites who use the crowd-sourced data to intervene and collaborate with other stakeholders. From our interviews, we identify the community, data, and action practices used by group administrators to collect, curate, and publish information about public safety that would otherwise go unreported. The combination of these practices improves the reputation of the groups on Facebook, increases trust, and encourages sustained participation from citizens. These practices also legitimize data gathered by group members as an important grassroots tool for responding to issues of public safety that would otherwise not be reported or acted upon. Our findings contribute a growing body of work that aims to understand how social media enable political action in contexts where people are not being served by existing institutions.
With Few Eyes, All Hoaxes are Deep
Authors: Asthana Sumit , Halfaker Aaron
Published: November 2018

Quality control is critical to open production communities like Wikipedia. Wikipedia editors enact border quality control with edits (counter-vandalism) and new article creations (new page patrolling) shortly after they are saved. In this paper, we describe a long-standing set of inefficiencies that have plagued new page patrolling by drawing a contrast to the more efficient, distributed processes for counter-vandalism. Further, to address this issue, we demonstrate an effective automated topic model based on a labeling strategy that leverages a folksonomy developed by subject specific working groups in Wikipedia (WikiProject tags) and a flexible ontology (WikiProjects Directory) to arrive at a hierarchical and uniform label set. We are able to attain very high fitness measures (macro ROC-AUC: 95.2%, macro PR-AUC: 74.5%) and real-time performance using word2vec-based features. Finally, we present a proposal for how incorporating this model into current tools will shift the dynamics of new article review positively.
Framing Effects
Authors: August Tal , Oliveira Nigini , Tan Chenhao , Smith Noah , Reinecke Katharina
Published: November 2018

Online experimentation with volunteers relies on participants' non-financial motivations to complete a study, such as to altruistically support science or to compare oneself to others. Researchers rely on these motivations to attract study participants and often use incentives, like performance comparisons, to encourage participation. Often, these study incentives are advertised using a slogan (e.g., "What is your thinking style?''). Research on framing effects suggests that advertisement slogans attract people with varying demographics and motivations. Could the slogan advertisements for studies risk attracting only specific users? To investigate the existence of potential sample biases, we measured how different slogan frames affected which participants self-selected into studies. We found that slogan frames impact recruitment significantly; changing the slogan frame from a 'supporting science' frame to a 'comparing oneself to others' frame lead to a 9% increase in recruitment for some studies. Additionally, slogans framed as learning more about oneself attract participants significantly more motivated by boredom compared to other slogan frames. We discuss design implications for using frames to improve recruitment and mitigate sources of sample bias in online research with volunteers.
#pray4victims
Authors: Buntain Cody L. , Lim Jung Kyu Rhys
Published: November 2018

This paper studies commonalities in response across disasters in online social networks (OSNs), specifically Twitter. After presenting an algorithm for extracting vocabularies across disasters, we extract type-specific vocabularies for terrorist attacks, earthquakes, and climate-related disasters between 2012 and 2017. Disaster type drives vocabulary similarity: terrorism responses mention an "attack" and law enforcement, earthquake responses mention the quake and its magnitude, and climate-related responses include safety and requests for aid. Across disaster types, tweets regularly mention victims/affected and prayer, consistent with communal coping and social support in crisis aftermath. Using disaster-type vocabularies, we study Twitter as a proxy for severity, correlating casualties to frequencies in Twitter. These vocabularies better correlate with casualties than baseline crisis lexica, especially in western countries. Twitter response and casualties diverge at the maximum, and Twitter response is stronger in Western countries, suggesting perceived severity is driven by additional factors.
UMI3D
Authors: Casarin Julien , Pacqueriaud Nicolas , Bechmann Dominique
Published: November 2018

UMI3D is a recent model which allows the generic description of 3D environments through a network. These generic environments can run outside of any device, on a server or on a separate computer. A unique dedicated application that we have named UMI3D client allows a VR, AR or MR device to interact with all the existing UMI3D environments. Moreover, the client-server architecture allows these environments to be collaborative. In this paper, we introduce a toolbox which allows the creation and running of UMI3D collaborative environments using Unity 3D. It contains tools to address the main concerns of computer-supported cooperative work (CSCW) systems in UMI3D environments. After introducing the contribution of this toolbox to the design of 3D CSCW systems, we present a user evaluation of an environment designed with this toolbox. Finally, we discuss the limits of the UMI3D model and the improvements that could be made to this model.
'Staged for Living'
Authors: Cheon EunJeong , Su Norman Makoto
Published: November 2018

We describe more than 19 months of ethnographic fieldwork with people who have embraced minimalism, a lifestyle movement focused on reducing modern life's clutter. We found that for minimalists, the home is a central but porous site for making and staging their values around objects. The home's porous boundary allows minimalists to reinforce their values around objects for others and themselves, but it also necessitates adopting strategies to assert their values when objects---entangled with others' values---move in and out the boundaries of the home. Drawing from our fieldwork, we introduce the concept of the porous boundary. "Porosity" impels us to consider the coupling of objects with values as we do boundary practices for the home. A porous boundary perspective, we argue, can open new design spaces in the development of novel technologies for the home.
Spacetime Characterization of Real-Time Collaborative Editing
Authors: D'Angelo Gabriele , Di Iorio Angelo , Zacchiroli Stefano
Published: November 2018

Real-Time Collaborative Editing (RTCE) is a popular way of instrumenting cooperative work on documents, in particular on the Web. Little is known in the literature yet about RTCE usage patterns in the real world. In this paper we study how a popular RTCE editor (Etherpad) is used in the wild, digging into the edit histories of a large collection of documents (about 14 000 pads), retrieved from one of the most popular public instances of the platform, hosted by the Wikimedia Foundation. The pad analysis is supported by a novel conceptual model that allows to label edit operations as "collaborative" or not depending on their distance-in edit position (space), edit time, or spacetime (both)-from edits made by other authors. The model is applied to classify all edits from the pad corpus. Classification results are further used to characterize the collaboration behavior of pad authors. Findings show that: 1) about half of the pads have a single author and hence witnessed no collaboration; 2) collaboration on common document parts happens often, but it happens asynchronously with authors taking turns in editing; and 3) simultaneous editing of common document parts happens very rarely. These findings help in revisiting early RTCE design decisions (e.g., the granularity of conflict management in RTCE protocols) and give insights on how to address novel needs (e.g., end-to-end encryption and offline editing).
Score-Group Framing Negatively Impacts Peer Evaluations
Authors: Durkin Celia , Rossano Federico , Klemmer Scott
Published: November 2018

How does group membership framing affect the feedback students provide learners? This paper presents two between-subjects experiments investigating the effect of Ingroup/Outgroup membership on effort spent in peer evaluations, and whether the group membership criterion type affects quality and stringency of evaluation. Two peer-review assignments were implemented in two separate classes. In the first study, students were nominally grouped by location they sat in class and non-nominally grouped by current class score; each was asked to review an Ingroup and Outgroup peer assignment. A second study randomly assigned students to one of four group types (random, score, motivation, and location); student reviewed two Ingroup assignments. In both studies, score-grouped students graded their peers more stringently than students grouped by location. These studies illustrate for system designers the impacts of group framing - and the disclosure of that-in peer review tasks.
Understanding Gender Equity in Author Order Assignment
Authors: Early Kirstin , Hammer Jessica , Hofmann Megan Kelly , Rode Jennifer A. , Wong Anna , Mankoff Jennifer
Published: November 2018

Women remain underrepresented in many fields in computer science, particularly at higher levels. In academia, success and promotion are influenced by a researcher's publication record. In many fields, including computer science, multi-author papers are the norm. Evidence from other fields shows that author order norms can influence the assignment of credit. We conduct interviews of students and faculty in human-computer interaction (HCI) and machine learning (ML) to determine factors related to assignment of author order in collaborative publication. The outcomes of these interviews then informed metrics of interest for a bibliometric analysis of gender and collaboration in research papers published from 1996 to 2016 in three top HCI and ML conferences. Based on our findings, we make recommendations for assignment of credit in multi-author papers and interpretation of author order, particularly in regard to how this area affects women.
Do Students' Learning Behaviors Differ when they Collaborate in Open-Ended Learning Environments?
Authors: Emara Mona , Rajendran Ramkumar , Biswas Gautam , Okasha Mahmod , Elbanna Adel Alsaeid
Published: November 2018

Researchers have long recognized the importance of using technology to support students' collaboration in learning and problem solving tasks. Recently, there has been a lot of research in capturing and characterizing student discourse and how they regulate each other when they perform learning tasks in pairs or in small groups. In this paper, our goal is to dive a little deeper into how students collaborate, and the learning behaviors they exhibit when working in pairs on a learning by modeling task, while also teaching a virtual agent in the Betty's Brain system. We report the results of a quasi-experimental study, where students were divided into two groups: one group worked in pairs and the other group worked individually. The results illustrate that students in the collaborative group built more correct causal maps than those working individually, and their pre-post test results show significantly higher learning gains in the science content. A differential sequence mining algorithm applied to their action sequences captured in log files showed differences in the learning behaviors between the two groups. The differences imply that the collaborative groups were better at debugging their evolving causal maps than the students who worked individually.
Beyond the Coded Gaze
Authors: Feuston Jessica L. , Piper Anne Marie
Published: November 2018

In CSCW and HCI, work examining expression of mental health and illness on social media frequently aims to classify content, quantify visual trends, and predict user states. This approach to analysis is a form of the coded gaze, a type of algorithmic 'way of seeing' coined with respect to artificial intelligence techniques. The coded gaze classifies content through researcher- and machine-labeled categories, relying on a series of theoretical assumptions that influence how values pertaining to mental health and illness become inscribed in data. In this paper, we build upon this research to support alternative methods of data interpretation. We join manual collection of Instagram posts with semi-structured interviews and digital ethnography over six months to understand how Instagram users express their experiences with mental health and illness. We argue that individuals negotiate claims to mental health and illness through visibility and signaling, the boundaries between mental health and illness are porous and blurred, and reposting and remix are a form of participation. We discuss practical and ethical implications for studying the expression of mental health and illness online.
'Welcome' Changes?
Authors: Morgan Jonathan T. , Filippova Anna
Published: November 2018

Open online communities rely on social norms for behavior regulation, group cohesion, and sustainability. Research on the role of social norms online has mainly focused on one source of influence at a time, making it difficult to separate different normative influences and understand their interactions. In this study, we use the Focus Theory to examine interactions between several sources of normative influence in a Wikipedia sub-community: local descriptive norms, local injunctive norms, and norms imported from similar sub-communities. We find that exposure to injunctive norms has a stronger effect than descriptive norms, that the likelihood of performing a behavior is higher when both injunctive and descriptive norms are congruent, and that conflicting social norms may negatively impact pro-normative behavior. We contextualize these findings through member interviews, and discuss their implications for both future research on normative influence in online groups and the design of systems that support open collaboration.
Gender, Feedback, and Learners' Decisions to Share Their Creative Computing Projects
Authors: Gan Emilia F. , Hill Benjamin Mako , Dasgupta Sayamindu
Published: November 2018

Although informal online learning communities are made possible by users' decisions to share their creations, participation by females and other marginalized groups remains stubbornly low in technical communities. Using descriptive statistics and a unique dataset of shared and unshared projects from over 1.1 million users of Scratch-a collaborative programming community for young people-we show that while girls share less initially, this trend flips among experienced users. Using Bayesian regression analyses, we show that this relationship can largely be attributed to differences in the way boys and girls participate. We also find that while prior positive feedback is correlated with increased sharing among inexperienced users, this effect also reverses with experience or with the addition of controls. Our findings provide a description of the dynamics behind online learners' decisions to share, open new research questions, and point to several lessons for system designers.
Social Photo-Elicitation
Authors: Gautam Aakash , Shrestha Chandani , Tatar Deborah , Harrison Steve
Published: November 2018

We report on an initial ethnographic exploration of the situation of sex-trafficking survivors in Nepal. In the course of studying trafficking survivors in a protected-living situation created by a non-governmental organization in Nepal, we adapted photo-elicitation to hear the voices of the survivors by making the technique more communal. Bringing sociality to the forefront of the method reduced the pressure on survivors to assert voices as individuals, allowing them to speak. We make three contributions to research. First, we propose a communal form of photo-elicitation as a method to elicit values in sensitive settings. Second, we present the complex circumstances of the survivors as they undergo rehabilitation and move towards life with a "new normal". Third, our work adds to HCI and CSCW literature on understanding specific concerns of trafficking survivors and aims to inform designs that can support reintegration of survivors in society. The values that the survivors hold and their notion of future opportunities suggest possession of limited but important social capital in some domains that could be leveraged to aid reintegration.
Eight Observations and 24 Research Questions About Open Source Projects
Authors: Germonprez Matt , Link Georg J.P. , Lumbard Kevin , Goggins Sean
Published: November 2018

The rapid acceleration of corporate engagement with open source projects is drawing out new ways for CSCW researchers to consider the dynamics of these projects. Research must now consider the complex ecosystems within which open source projects are situated, including issues of for-profit motivations, brokering foundations, and corporate collaboration. Localized project considerations cannot reveal broader workings of an open source ecosystem, yet much empirical work is constrained to a local context. In response, we present eight observations from our eight-year engaged field study about the changing nature of open source projects. We ground these observations through 24 research questions that serve as primers to spark research ideas in this new reality of open source projects. This paper contributes to CSCW in social and crowd computing by delivering a rich and fresh look at corporately-engaged open source projects with a call for renewed focus and research into newly emergent areas of interest.
Fake Cures
Authors: Ghenai Amira , Mejova Yelena
Published: November 2018

Social media's unfettered access has made it an important venue for health discussion and a resource for patients and their loved ones. However, the quality of information available, as well as the motivations of its posters, has been questioned. This work examines the individuals on social media that are posting questionable health-related information, and in particular promoting cancer treatments which have been shown to be ineffective (making it a kind of misinformation, willful or not). Using a multi-stage user selection process, we study 4,212 Twitter users who have posted about one of 139 such "treatments", and compare them to a baseline of users generally interested in cancer. Considering features capturing user attributes, writing style, and sentiment, we build a classifier which is able to identify users prone to propagate such misinformation at an accuracy of over 90%, providing a potential tool for public health officials to identify such individuals for preventive intervention.
Personalized Motivation-supportive Messages for Increasing Participation in Crowd-civic Systems
Authors: Grau Paul , Naderi Babak , Kim Juho
Published: November 2018

In crowd-civic systems, citizens form groups and work towards shared goals, such as discovering social issues or reforming official policies. Unfortunately, many real-world systems have been unsuccessful in continually motivating large numbers of citizens to participate voluntarily, despite various approaches such as gamification and persuasion techniques. In this paper, we examine the influence of personalized messages designed to support motivation as asserted by the Self-Determination Theory (SDT). We designed a crowd-civic platform for collecting community issues with personalized motivation-supportive messages and conducted two studies: a pair-comparison experiment with 150 participants on Amazon's Mechanical Turk and a live deployment study with 120 university members. Results of the pair-comparison study indicate applicability of SDT's perspective in crowd-civic systems. While applying it in the live system surfaced several challenges, including recruiting participants without interfering with general motivations, the collected data exhibited similar promising trends.
Productivity in an Era of Multi-Teaming
Authors: Gupta Pranav , Woolley Anita Williams
Published: November 2018

When and why do information dashboards enhance team productivity? We explore this question in the context of project teams whose members have to work across multiple teams at the same time. We expected multi-teaming, especially that involving a high variety in team members, would have a negative effect on team performance by impairing a team's transactive memory system (TMS), a critical form of shared cognition allowing members to keep track of who knows what. Further, we expected the use of an information dashboard with member skills could combat the harmful effects of high-variety multi-teaming. To test our hypotheses experimentally, we developed an online game (Knowledge Worker's Dilemma) that simulates the coordination decisions that professionals face in app development teams. Results show multi-teaming hurt team performance by reducing TMS; use of an information dashboard benefited high-variety teams and, surprisingly, hurt the performance of low-variety teams. Potential explanations and implications are discussed.
Bot Detection in Wikidata Using Behavioral and Other Informal Cues
Authors: Hall Andrew , Terveen Loren , Halfaker Aaron
Published: November 2018

Bots have been important to peer production's success. Wikipedia, OpenStreetMap, and Wikidata all have taken advantage of automation to perform work at a rate and scale exceeding that of human contributors. Understanding the ways in which humans and bots behave in these communities is an important topic, and one that relies on accurate bot recognition. Yet, in many cases, bot activities are not explicitly flagged and could be mistaken for human contributions. We develop a machine classifier to detect previously unidentified bots using implicit behavioral and other informal editing characteristics. We show that this method yields a high level of fitness under both formal evaluation (PR-AUC: 0.845, ROC-AUC: 0.985) and a qualitative analysis of "anonymous" contributor edit sessions. We also show that, in some cases, unflagged bot activities can significantly misrepresent human behavior in analyses. Our model has the potential to support future research and community patrolling activities.
Going Beyond Obscurity
Authors: Hargitai Viktor , Shklovski Irina , Wasowski Andrzej
Published: November 2018

Anonymization is viewed as a solution to over-exposure of personal information in a data-driven society. Yet how organizations apply anonymization techniques to data for regulatory, ethical or commercial reasons remains underexplored. We investigate how such measures are applied in organizations, asking whether anonymization practices are used, what approaches are considered practical and adequate, and how decisions are made to protect the privacy of data subjects while preserving analytical value. Our findings demonstrate that anonymization is applied to data far less pervasively than expected. Organizations that do employ anonymization often view their practices as sensitive and resort to anonymity by obscurity alongside technical means. Rather than being a purely technical question of applying the right algorithms, anonymization in practice is a complex socio-technical process that relies on multi-stakeholder collaborations. Organizational decision-making about appropriate approaches and the management of responsibility can result in workarounds necessary to negotiate the technical complexity.
Emotional Biosensing
Authors: Howell Noura , Chuang John , De Kosnik Abigail , Niemeyer Greg , Ryokai Kimiko
Published: November 2018

Emotional biosensing is rising in daily life: Data and categories claim to know how people feel and suggest what they should do about it, while CSCW explores new biosensing possibilities. Prevalent approaches to emotional biosensing are too limited, focusing on the individual, optimization, and normative categorization. Conceptual shifts can help explore alternatives: toward materiality, from representation toward performativity, inter-action to intra-action, shifting biopolitics, and shifting affect/desire. We contribute (1) synthesizing wide-ranging conceptual lenses, providing analysis connecting them to emotional biosensing design, (2) analyzing selected design exemplars to apply these lenses to design research, and (3) offering our own recommendations for designers and design researchers. In particular we suggest humility in knowledge claims with emotional biosensing, prioritizing care and affirmation over self-improvement, and exploring alternative desires. We call for critically questioning and generatively re-imagining the role of data in configuring sensing, feeling, 'the good life,' and everyday experience.
Deliberation and Resolution on Wikipedia
Authors: Im Jane , Zhang Amy X. , Schilling Christopher J. , Karger David
Published: November 2018

Resolving disputes in a timely manner is crucial for any online production group. We present an analysis of Requests for Comments (RfCs), one of the main vehicles on Wikipedia for formally resolving a policy or content dispute. We collected an exhaustive dataset of 7,316 RfCs on English Wikipedia over the course of 7 years and conducted a qualitative and quantitative analysis into what issues affect the RfC process. Our analysis was informed by 10 interviews with frequent RfC closers. We found that a major issue affecting the RfC process is the prevalence of RfCs that could have benefited from formal closure but that linger indefinitely without one, with factors including participants' interest and expertise impacting the likelihood of resolution. From these findings, we developed a model that predicts whether an RfC will go stale with 75.3% accuracy, a level that is approached as early as one week after dispute initiation.
Engaging Solidarity in Data Collection Practices for Community Health
Authors: Ismail Azra , Kumar Neha
Published: November 2018

Researchers and practitioners engaged in global health are increasingly turning to data-driven approaches. However, the institutionalized roles and responsibilities---as well as motivations and workflows---of those involved in data collection are not well understood. To attain a deeper understanding of the practices of frontline health workers engaged in data collection, we conducted fieldwork in underserved contexts of Delhi, India. In particular, we interviewed these workers and observed their interactions with 200 households. Our analysis takes a postcolonial feminist perspective to examine how these frontline health workers navigate the multiple demands placed on them by their families, society, local residents, and health organizations. We also discuss how they practice feminist solidarity, and distill lessons for improved data collection across global health initiatives.
MyPath
Authors: Jacobs Maia , Johnson Jeremy , Mynatt Elizabeth D.
Published: November 2018

Following a cancer diagnosis, patients must cope with numerous physical, emotional, and practical challenges. While health information exists to help patients learn how to manage these challenges, health information seeking often declines over time, recalling information is difficult, and limited time with healthcare providers can leave patients feeling uninformed about their illness. We designed MyPath to overcome these information access challenges. The mobile system offers personalized, dynamic, and trusted health information recommendations to help patients learn about and manage their cancer. Through a seven-month deployment study with breast cancer patients, we found that use of the application encouraged proactive health management behaviors, and identified factors that motivated technology adoption and abandonment. We discuss the implications of these results for facilitating use of mHealth tools by a rural patient population and the importance of scaling support to a large range of information needs. We use this work to demonstrate the value of personalized health information systems and to motivate future CSCW research developing personalized support systems for other health situations with complex information access models.
ScamCoins, S*** Posters, and the Search for the Next Bitcoin
TM
Authors: Jahani Eaman , Krafft Peter M. , Suhara Yoshihiko , Moro Esteban , Pentland Alex Sandy
Published: November 2018

Participants in cryptocurrency markets are in constant communication with each other about the latest coins and news releases. Do these conversations build hype through the contagiousness of excitement, help the community process information, or play some other role? Using a novel dataset from a major cryptocurrency forum, we conduct an exploratory study of the characteristics of online discussion around cryptocurrencies. Through a regression analysis, we find that coins with more information available and higher levels of technical innovation are associated with higher quality discussion. People who talk about "serious" coins tend to participate in discussion displaying signatures of collective intelligence and information processing, while people who talk about "less serious" coins tend to display signatures of hype and naïvety. Interviews with experienced forum members also confirm these quantitative findings. These results highlight the varied roles of discussion in the cryptocurrency ecosystem and suggest that discussion of serious coins may be oriented towards earnest, perhaps more accurate, attempts at discovering which coins are likely to succeed.
Neighbourhood Data
Authors: Johnson Ian G. , Puussaar Aare , Manuel Jennifer , Wright Peter
Published: November 2018

There is a growing public, political, and academic discourse around the idea that data has the potential to empower citizens. In particular, evidence-based policymaking is at the centre of national and regional planning processes. At the same time a shift towards Localism in planning means that while citizens and civic groups are centrally involved in decision-making about their communities, they lack the skills, resources and access to data that might inform their decision-making. There is a need to establish new ways of supporting deliberation and decision-making in local planning. We report a study that explores the role of data in the complex processes involved in consultation events and the broader collaborative processes surrounding them. In doing so we highlight the need for the integration of dialogic forms of participation with other locally produced data, and for this to be shared in ways that position data as a resource for action.