bluuebunny/crossref_metadata_2025 huggingface dataset:
Paying Crowd Workers for Collaborative Work
Authors: d'Eon Greg , Goh Joslin , Larson Kate , Law Edith
Published: November 2019

Collaborative crowdsourcing tasks allow crowd workers to solve problems that they could not handle alone, but worker motivation in these tasks is not well understood. In this paper, we study how to motivate groups of workers by paying them equitably. To this end, we characterize existing collaborative tasks based on the types of information available to crowd workers. Then, we apply concepts from equity theory to show how fair payments relate to worker motivation, and we propose two theoretically grounded classes of fair payments. Finally, we run two experiments using an audio transcription task on Amazon Mechanical Turk to understand how workers perceive these payments. Our results show that workers recognize fair and unfair payment divisions, but are biased toward payments that reward them more. Additionally, our data suggests that fair payments could lead to a small increase in worker effort. These results inform the design of future collaborative crowdsourcing tasks.
Disinformation as Collaborative Work
Authors: Starbird Kate , Arif Ahmer , Wilson Tom
Published: November 2019

In this paper, we argue that strategic information operations (e.g. disinformation, political propaganda, and other forms of online manipulation) are a critical concern for CSCW researchers, and that the CSCW community can provide vital insight into understanding how these operations function-by examining them as collaborative "work" within online crowds. First, we provide needed definitions and a framework for conceptualizing strategic information operations, highlighting related literatures and noting historical context. Next, we examine three case studies of online information operations using a sociotechnical lens that draws on CSCW theories and methods to account for the mutual shaping of technology, social structure, and human action. Through this lens, we contribute a more nuanced understanding of these operations (beyond "bots" and "trolls") and highlight a persistent challenge for researchers, platform designers, and policy makers-distinguishing between orchestrated, explicitly coordinated, information operations and the emergent, organic behaviors of an online crowd.
"Privacy is not a concept, but a way of dealing with life"
Authors: Jack Margaret C. , Sovannaroth Pang , Dell Nicola
Published: November 2019

Privacy scholarship has shown how norms of appropriate information flow and information regulatory processes vary according to environment, which change as the environment changes, including through the introduction of new technologies. This paper describes findings from a qualitative research study that examines practices and perceptions of privacy in Cambodia as the population rapidly moves into an online environment (specifically Facebook, the most popular Internet tool in Cambodia today). We empirically demonstrate how the concept of privacy differs across cultures and show how the Facebook platform, as it becomes popular worldwide, catalyzes change in norms of information regulation. We discuss how the localization of transnational technology platforms provides a key site in which to investigate changing cultural ideas about privacy, and to discover misalignments between different expectations for information flow. Finally, we explore ways that insufficient localization effort by transnational technology companies puts some of the most marginalized users at disproportionate information disclosure risk when using new Internet tools, and offer some pragmatic suggestions for how such companies could improve privacy tools for users who are far -geographically or culturally - from where the tools are designed.
Managing Stress
Authors: Zolyomi Annuska , Begel Andrew , Waldern Jennifer Frances , Tang John , Barnett Michael , Cutrell Edward , McDuff Daniel , Andrist Sean , Morris Meredith Ringel
Published: November 2019

Video calling (VC) aims to create multi-modal, collaborative environments that are "just like being there." However, we found that autistic individuals, who exhibit atypical social and cognitive processing, may not share this goal. We interviewed autistic adults about their perceptions of VC compared to other computer- mediated communications (CMC) and face-to-face interactions. We developed a neurodiversity-sensitive model of CMC that describes how stressors such as sensory sensitivities, cognitive load, and anxiety, contribute to their preferences for CMC channels. We learned that they apply significant effort to construct coping strategies to support their sensory, cognitive, and social needs. These strategies include moderating their sensory inputs, creating mental models of conversation partners, and attempting to mask their autism by adopting neurotypical behaviors. Without effective strategies, interviewees experience more stress, have less capacity to interpret verbal and non-verbal cues, and feel less empowered to participate. Our findings reveal critical needs for autistic users. We suggest design opportunities to support their ability to comfortably use VC, and in doing so, point the way towards making VC more comfortable for all.
Self-declared Throwaway Accounts on Reddit
Authors: Ammari Tawfiq , Schoenebeck Sarita , Romero Daniel
Published: November 2019

Parents can be subjected to scrutiny and judgment for their parenting choices. Much of this scrutiny is experienced online, especially around stigmatized topics such as divorce, custody, postpartum depression, and miscarriage. Prior theory suggests that parents might be able to access greater support online when anonymous, but other evidence suggests that anonymity may increase bad behavior. Drawing from ten years of Reddit parenting boards, we show that parents are more likely to discuss potentially stigmatizing topics using anonymous ("throwaway") accounts. We find that, on average, throwaway comments are more likely to receive a response, receive more responses that are longer, and receive responses that have higher karma scores than topically similar comments posted by non-throwaway accounts. We argue that self-identified throwaway accounts provide a crucial environment for supporting parents with stigmatizing experiences. They also provide a shared platform signal (the throwaway account) which enables other Reddit users to access shared experiences and support. We propose that a hybrid combination of identified and anonymous platforms could provide more supportive online experiences for parents and other users.
When Users Control the Algorithms
Authors: Burrell Jenna , Kahn Zoe , Jonas Anne , Griffin Daniel
Published: November 2019

Recent interest in ethical AI has brought a slew of values, including fairness, into conversations about technology design. Research in the area of algorithmic fairness tends to be rooted in questions of distribution that can be subject to precise formalism and technical implementation. We seek to expand this conversation to include the experiences of people subject to algorithmic classification and decision-making. By examining tweets about the "Twitter algorithm" we consider the wide range of concerns and desires Twitter users express. We find a concern with fairness (narrowly construed) is present, particularly in the ways users complain that the platform enacts a political bias against conservatives. However, we find another important category of concern, evident in attempts to exert control over the algorithm. Twitter users who seek control do so for a variety of reasons, many well justified. We argue for the need for better and clearer definitions of what constitutes legitimate and illegitimate control over algorithmic processes and to consider support for users who wish to enact their own collective choices.
How Computers See Gender
Authors: Scheuerman Morgan Klaus , Paul Jacob M. , Brubaker Jed R.
Published: November 2019

Investigations of facial analysis (FA) technologies-such as facial detection and facial recognition-have been central to discussions about Artificial Intelligence's (AI) impact on human beings. Research on automatic gender recognition, the classification of gender by FA technologies, has raised potential concerns around issues of racial and gender bias. In this study, we augment past work with empirical data by conducting a systematic analysis of how gender classification and gender labeling in computer vision services operate when faced with gender diversity. We sought to understand how gender is concretely conceptualized and encoded into commercial facial analysis and image labeling technologies available today. We then conducted a two-phase study: (1) a system analysis of ten commercial FA and image labeling services and (2) an evaluation of five services using a custom dataset of diverse genders using self-labeled Instagram images. Our analysis highlights how gender is codified into both classifiers and data standards. We found that FA services performed consistently worse on transgender individuals and were universally unable to classify non-binary genders. In contrast, image labeling often presented multiple gendered concepts. We also found that user perceptions about gender performance and identity contradict the way gender performance is encoded into the computer vision infrastructure. We discuss our findings from three perspectives of gender identity (self-identity, gender performativity, and demographic identity) and how these perspectives interact across three layers: the classification infrastructure, the third-party applications that make use of that infrastructure, and the individuals who interact with that software. We employ Bowker and Star's concepts of "torque" and "residuality" to further discuss the social implications of gender classification. We conclude by outlining opportunities for creating more inclusive classification infrastructures and datasets, as well as with implications for policy.
Measuring the Effects of Gender on Online Social Conformity
Authors: Wijenayake Senuri , van Berkel Niels , Kostakos Vassilis , Goncalves Jorge
Published: November 2019

Social conformity occurs when an individual changes their behaviour in line with the majority's expectations. Although social conformity has been investigated in small group settings, the effect of gender - of both the individual and the majority/minority - is not well understood in online settings. Here we systematically investigate the impact of groups' gender composition on social conformity in online settings. We use an online quiz in which participants submit their answers and confidence scores, both prior to and following the presentation of peer answers that are dynamically fabricated. Our results show an overall conformity rate of 39%, and a significant effect of gender that manifests in a number of ways: gender composition of the majority, the perceived nature of the question, participant gender, visual cues of the system, and final answer correctness. We conclude with a discussion on the implications of our findings in designing online group settings, accounting for the effects of gender on conformity.
Co-designing for Community Oversight
Authors: Chouhan Chhaya , LaPerriere Christy M. , Aljallad Zaina , Kropczynski Jess , Lipford Heather , Wisniewski Pamela J.
Published: November 2019

Collective feedback can support an individual's decision-making process. For instance, individuals often seek the advice of friends, family, and co-workers to help them make privacy decisions. However, current technologies often do not provide mechanisms for this type of collaborative interaction. To address this gap, we propose a novel model of Community Oversight for Privacy and Security ("CO-oPS"), which identifies mechanisms for users to interact with people they trust to help one another make digital privacy and security decisions. We apply our CO-oPS model in the context of mobile applications ("apps"). To interrogate and refine this model, we conducted participatory design sessions with 32 participants in small groups of 2-4 people who know one another, with the goal of designing a mobile app that facilitates collaborative privacy and security decision-making. We describe and reflect on the opportunities and challenges that arise from the unequal motivation and trust in seeking support and giving support within and beyond a community. Through this research, we contribute a novel framework for collaborative digital privacy and security decision-making and provide empirical evidence towards how researchers and designers might translate this framework into design-based features.
Who is the "Human" in Human-Centered Machine Learning
Authors: Chancellor Stevie , Baumer Eric P. S. , De Choudhury Munmun
Published: November 2019

"Human-centered machine learning" (HCML) combines human insights and domain expertise with data-driven predictions to answer societal questions. This area's inherent interdisciplinarity causes tensions in the obligations researchers have to the humans whose data they use. This paper studies how scientific papers represent human research subjects in HCML. Using mental health status prediction on social media as a case study, we conduct thematic discourse analysis on 55 papers to examine these representations. We identify five discourses that weave a complex narrative of who the human subject is in this research: Disorder/Patient, Social Media, Scientific, Data/Machine Learning, and Person. We show how these five discourses create paradoxical subject and object representations of the human, which may inadvertently risk dehumanization. We also discuss the tensions and impacts of interdisciplinary research; the risks of this work to scientific rigor, online communities, and mental health; and guidelines for stronger HCML research in this nascent area.
Joining Together Online
Authors: Harris Alexa M. , Gómez-Zará Diego , DeChurch Leslie A. , Contractor Noshir S.
Published: November 2019

The field of Computer Supported Cooperative Work (CSCW) has an enduring interest in studying and designing technologies that bring people together in partnerships, teams, crowds, communities, and other collectives. As the technologies enabling group formation have evolved, so too have the guiding questions pursued by CSCW scholars. This review outlines the trajectory of scholarship on group formation with an eye towards the most pressing future questions in this area. To understand how CSCW researchers have studied technology-enabled group formation, we systematically review articles published at CSCW from 1992 to 2018. Exploring more than 2,000 potentially relevant works, we identified 35 focused on technologies and group formation. Content coding and thematic analysis revealed four periods and six themes in the study of online group formation. These themes include: group composition, self-presentation, assembly mechanisms, recruitment, organizing structures, and group culture. Quo vadis? Based on our review, we offer recommendations for the next generation of CSCW scholarship seeking to understand and enable collectives joining together online.
Does Transparency in Moderation Really Matter?
Authors: Jhaver Shagun , Bruckman Amy , Gilbert Eric
Published: November 2019

When posts are removed on a social media platform, users may or may not receive an explanation. What kinds of explanations are provided? Do those explanations matter? Using a sample of 32 million Reddit posts, we characterize the removal explanations that are provided to Redditors, and link them to measures of subsequent user behaviors---including future post submissions and future post removals. Adopting a topic modeling approach, we show that removal explanations often provide information that educate users about the social norms of the community, thereby (theoretically) preparing them to become a productive member. We build regression models that show evidence of removal explanations playing a role in future user activity. Most importantly, we show that offering explanations for content moderation reduces the odds of future post removals. Additionally, explanations provided by human moderators did not have a significant advantage over explanations provided by bots for reducing future post removals. We propose design solutions that can promote the efficient use of explanation mechanisms, reflecting on how automated moderation tools can contribute to this space. Overall, our findings suggest that removal explanations may be under-utilized in moderation practices, and it is potentially worthwhile for community managers to invest time and resources into providing them.
Modeling Islamist Extremist Communications on Social Media using Contextual Dimensions
Authors: Kursuncu Ugur , Gaur Manas , Castillo Carlos , Alambo Amanuel , Thirunarayan Krishnaprasad , Shalin Valerie , Achilov Dilshod , Arpinar I. Budak , Sheth Amit
Published: November 2019

Terror attacks have been linked in part to online extremist content. Online conversations are cloaked in religious ambiguity, with deceptive intentions, often twisted from mainstream meaning to serve a malevolent ideology. Although tens of thousands of Islamist extremism supporters consume such content, they are a small fraction relative to peaceful Muslims. The efforts to contain the ever-evolving extremism on social media platforms have remained inadequate and mostly ineffective. Divergent extremist and mainstream contexts challenge machine interpretation, with a particular threat to the precision of classification algorithms. Radicalization is a subtle long-running persuasive process that occurs over time. Our context-aware computational approach to the analysis of extremist content on Twitter breaks down this persuasion process into building blocks that acknowledge inherent ambiguity and sparsity that likely challenge both manual and automated classification. Based on prior empirical and qualitative research in social sciences, particularly political science, we model this process using a combination of three contextual dimensions -- religion, ideology, and hate -- each elucidating a degree of radicalization and highlighting independent features to render them computationally accessible. We utilize domain-specific knowledge resources for each of these contextual dimensions such as Qur'an for religion, the books of extremist ideologues and preachers for political ideology and a social media hate speech corpus for hate. The significant sensitivity of the Islamist extremist ideology and its local and global security implications require reliable algorithms for modelling such communications on Twitter. Our study makes three contributions to reliable analysis: (i) Development of a computational approach rooted in the contextual dimensions of religion, ideology, and hate, which reflects strategies employed by online Islamist extremist groups, (ii) An in-depth analysis of relevant tweet datasets with respect to these dimensions to exclude likely mislabeled users, and (iii) A framework for understanding online radicalization as a process to assist counter-programming. Given the potentially significant social impact, we evaluate the performance of our algorithms to minimize mislabeling, where our context-aware approach outperforms a competitive baseline by 10.2% in precision, thereby enhancing the potential of such tools for use in human review.
Balancing Tensions between Caregiving and Parenting Responsibilities in Pediatric Patient Care
Authors: Seo Woosuk , Berry Andrew B.L. , Bhagane Prachi , Choi Sung Won , Buyuktur Ayse G. , Park Sun Young
Published: November 2019

In pediatric chronic care, the treatment process affects not just the child's physical health, but his or her psychosocial and emotional development. As a result, caring for pediatric patients with a chronic illness such as cancer is becoming a daunting task for parental caregivers. They are expected to fulfill the caregiving needs of managing the child's health condition and treatment while also meeting the parenting needs of translating knowledge, communicating about the illness, and making numerous decisions on a daily basis for their sick child due to the child's young age. Drawing on 15 semi-structured interviews, we examined parental caregivers' perspectives on raising a child while also managing the child's health. We identified three tensions that participants encountered as they balanced parenting and caregiving responsibilities: (i) tension between ensuring the child's health and safety and attending to the child's social development, (ii) tension between disclosing health-related information and minimizing the psychological burden on the child, and (iii) tension between rewarding the child's cooperation in treatment and maintaining discipline. Together, these tensions reveal an ongoing process through which caregivers assess and interpret their actions and responsibilities relative to anticipated consequences across multiple time scales. These findings reveal opportunities for sociotechnical systems to account for and support this active process of iterative cycles of assessment.
Boundary Negotiation for Patient-Provider Communication via WeChat in China
Authors: Ding Xianghua , Chen Yunan , Ding Zhaofei , Xu Yiwen
Published: November 2019

Patient-Provider Communication (PPC) is crucial to the quality and outcome of healthcare practices. With the development of Information and Communication Technologies (ICTs), ICT mediated PPC has become increasingly commonplace, and has been extensively studied. However, prior research has primarily focused on the institutional use of ICTs for PPC, with institutional support and regulation, while the personal use of ICTs for this purpose has been mostly under-explored. This paper presents a qualitative study of the use of WeChat, a general mobile social application, that has been personally appropriated for PPC in China. Sixteen patients and seven physicians, who had experience using WeChat for PPC, were recruited and interviewed to gain an understanding from both perspectives on how WeChat was utilized for the communication purposes between them. We found that the use of WeChat helped to strengthen the relationship between patients and providers, and provided a psychological reassurance that the structure of the current Chinese health system doesn't provide. Most importantly, we found that the use of WeChat was dependent on the negotiation and management of boundaries that address various concerns associated with the use of ICTs for PPC, such as workload and safety. In this paper, we will highlight the boundary negotiation practices and discuss implications based on the findings.
When Knowledge Network is Social Network
Authors: Yang Chi-Lan , Yuan Chien Wen (Tina) , Wang Hao-Chuan
Published: November 2019

In workplaces, knowledge has the property of being individually kept and collectively shared. It is distributed and embedded among members but needs to be transferred and pooled through knowledge networks for successful collaboration. In order to understand and embody such networks, we employed a mixture of field observations, social network analysis, and in-depth interviews to examine the practices of knowledge transfer in a local financial institute (N=32). Results from the analyses show that there is a discrepancy between inbound and outbound knowledge transfer, and also suggest that expertise or social relation cannot solely account for members' decision on whom to ask questions and share knowledge. We also found that scaffolding workers to connect to the right person with metaknowledge of the knowledge network is important. Our findings point to research and design opportunities to support knowledge transfer at the collaborative level within a knowledge community.
Of Ulti, 'hajano', and "Matachetar otanetak datam"
Authors: Haque S M Taiabul , Saha Pratyasha , Rahman Muhammad Sajidur , Ahmed Syed Ishtiaque
Published: November 2019

Strategies of hiding information over communication media have long been an interest of CSCW and related communities. Most of the studies in this area have focused on various computational means of data protection and their vulnerabilities, and occasionally on social practices situated in the West. However, communities in the Global South often have a rich trove of vernacular arts and crafts of hiding information that might be leveraged to design novel kinds of privacy-preserving technologies. In this paper, we present findings from our three-month long original ethnographic work with various communities in Dhaka, Bangladesh that reveal a wide range of culturally embedded techniques of hiding confidential and sensitive information from their 'others'. Our analysis demonstrates the dynamic nature of these techniques, the learning process associated with them, and their deep relationship with contextual politics that these communities are embedded in. We further connect our findings to the broader interests of CSCW around otherness, ethics, and democracy, and also discuss their implications for design.
Making a "Pro": 'Professionalism' after Platforms in Beauty-work
Authors: Raval Noopur , Pal Joyojeet
Published: November 2019

Beauty and Wellness work in India happen largely in the informal sector and are heavily gendered forms of work. The arrival of app-based on-demand platforms that aggregate beauticians and spa therapists to provide at-home services in urban India have aimed to create new efficiencies in this work, providing both the service providers and users of these with new means of transacting. This paper presents findings from an ethnographic study of an app-based platform that provides beauty and wellness services. We interviewed stakeholders including platform company employees, customers, beauty-trainers as well as platform-workers. Our results show the ways in which technology is creating new expectations around professionalism and training, which intersect with the ways workspaces and provider-receiver relationships are articulated around wellness work in urban India. We argue that this case offers an insightful example into the future of work - specifically platform work's attempts to create entrepreneurial subjects, and its tensions with the realities of gender, class and caste as they relate to care labor in India.
Procedural Justice in Algorithmic Fairness
Authors: Lee Min Kyung , Jain Anuraag , Cha Hea Jin , Ojha Shashank , Kusbit Daniel
Published: November 2019

As algorithms increasingly take managerial and governance roles, it is ever more important to build them to be perceived as fair and adopted by people. With this goal, we propose a procedural justice framework in algorithmic decision-making drawing from procedural justice theory, which lays out elements that promote a sense of fairness among users. As a case study, we built an interface that leveraged two key elements of the framework---transparency and outcome control---and evaluated it in the context of goods division. Our interface explained the algorithm's allocative fairness properties (standards clarity) and outcomes through an input-output matrix (outcome explanation), then allowed people to interactively adjust the algorithmic allocations as a group (outcome control). The findings from our within-subjects laboratory study suggest that standards clarity alone did not increase perceived fairness; outcome explanation had mixed effects, increasing or decreasing perceived fairness and reducing algorithmic accountability; and outcome control universally improved perceived fairness by allowing people to realize the inherent limitations of decisions and redistribute the goods to better fit their contexts, and by bringing human elements into final decision-making.
Understanding Family Collaboration Around Lightweight Modification of Everyday Objects in the Home
Authors: Williams Kristin , Pulivarthy Rajitha , Hudson Scott E. , Hammer Jessica
Published: November 2019

The internet-of-things (IoT) carries substantial costs by urging households to replace their possessions with new, internet connected versions of everyday objects. Beyond financial, these costs include waste, work to arrange and orchestrate objects to suit households, and that of acquiring new skills. Upcycling domestic objects could offer households greater discretion and control over these costs by supporting the ability to tailor IoT to the home. To understand how households might do this, we conducted a home study with 10 diverse American households over 7 days to surface the approaches families are likely to use when tailoring IoT to their existing possessions. We asked family members to enact their process using endowed sticker props---IoT Stickers---to modify objects in their home. We develop a framework of how families make light weight modifications of domestic possessions, summarize trends of their object modifications, and describe the burdens such a system could impose.
Intergroup Contact in the Wild
Authors: Zhang Jason Shuo , Tan Chenhao , Lv Qin
Published: November 2019

Intergroup contact has long been considered as an effective strategy to reduce prejudice between groups. However, recent studies suggest that exposure to opposing groups in online platforms can exacerbate polarization. To further understand the behavior of individuals who actively engage in intergroup contact in practice, we provide a large-scale observational study of intragroup behavioral differences between members with and without intergroup contact. We leverage the existing structure of NBA-related discussion forums on Reddit to study the context of professional sports. We identify fans of each NBA team as members of a group and trace whether they have intergroup contact. Our results show that members with intergroup contact use more negative and abusive language in their affiliated group than those without such contact, after controlling for activity levels. We further quantify different levels of intergroup contact and show that there may exist nonlinear mechanisms regarding how intergroup contact relates to intragroup behavior. Our findings provide complementary evidence to experimental studies in a novel context and also shed light on possible reasons for the different outcomes in prior studies.
I Say, You Say, We Say
Authors: Stewart Angela E.B. , Vrzakova Hana , Sun Chen , Yonehiro Jade , Stone Cathlyn Adele , Duran Nicholas D. , Shute Valerie , D'Mello Sidney K.
Published: November 2019

Collaborative problem solving (CPS) is a crucial 21st century skill; however, current technologies fall short of effectively supporting CPS processes, especially for remote, computer-enabled interactions. In order to develop next-generation computer-supported collaborative systems that enhance CPS processes and outcomes by monitoring and responding to the unfolding collaboration, we investigate automated detection of three critical CPS process ? construction of shared knowledge, negotiation/coordination, and maintaining team function ? derived from a validated CPS framework. Our data consists of 32 triads who were tasked with collaboratively solving a challenging visual computer programming task for 20 minutes using commercial videoconferencing software. We used automatic speech recognition to generate transcripts of 11,163 utterances, which trained humans coded for evidence of the above three CPS processes using a set of behavioral indicators. We aimed to automate the trained human-raters' codes in a team-independent fashion (current study) in order to provide automatic real-time or offline feedback (future work). We used Random Forest classifiers trained on the words themselves (bag of n-grams) or with word categories (e.g., emotions, thinking styles, social constructs) from the Linguistic Inquiry Word Count (LIWC) tool. Despite imperfect automatic speech recognition, the n-gram models achieved AUROC (area under the receiver operating characteristic curve) scores of .85, .77, and .77 for construction of shared knowledge, negotiation/coordination, and maintaining team function, respectively; these reflect 70%, 54%, and 54% improvements over chance. The LIWC-category models achieved similar scores of .82, .74, and .73 (64%, 48%, and 46% improvement over chance). Further, the LIWC model-derived scores predicted CPS outcomes more similar to human codes, demonstrating predictive validity. We discuss embedding our models in collaborative interfaces for assessment and dynamic intervention aimed at improving CPS outcomes.
Discovering the Sweet Spot of Human-Computer Configurations
Authors: Mackeprang Maximilian , Müller-Birn Claudia , Stauss Maximilian Timo
Published: November 2019

Interactive intelligent systems, i.e., interactive systems that employ AI technologies, are currently present in many parts of our social, public and political life. An issue reoccurring often in the development of these systems is the question regarding the level of appropriate human and computer contributions. Engineers and designers lack a way of systematically defining and delimiting possible options for designing such systems in terms of levels of automation. In this paper, we propose, apply and reflect on a method for human-computer configuration design. It supports the systematic investigation of the design space for developing an interactive intelligent system. We illustrate our method with a use case in the context of collaborative ideation. Here, we developed a tool for information extraction from idea content. A challenge was to find the right level of algorithmic support, whereby the quality of the information extraction should be as high as possible, but, at the same time, the human effort should be low. Such contradicting goals are often an issue in system development; thus, our method proposed helped us to conceptualize and explore the design space. Based on a critical reflection on our method application, we want to offer a complementary perspective to the value-centered design of interactive intelligent systems. Our overarching goal is to contribute to the design of so-called hybrid systems where humans and computers are partners.
Quantification of Gender Representation Bias in Commercial Films based on Image Analysis
Authors: Jang Ji Yoon , Lee Sangyoon , Lee Byungjoo
Published: November 2019

In film directing, a bias towards the representation of a particular gender can cause the audience to form a distorted stereotype of the gender role. The Bechdel test has been widely used to objectively judge the existence of such bias in films. However, because its analysis is based solely on the script of a film, the Bechdel test is incapable of considering the broad spectrum of bias that films can have as a visual medium. This study proposes a more comprehensive analysis system that quantifies the degree of bias in the visual representations of female and male characters in commercial films. By analyzing the image frames of a movie using the latest image analysis techniques, a total of 40 films were analyzed based on 8 quantitative indices. The result demonstrates that there exists a statistically significant difference in the visual representation of female and male characters. Specifically, female characters showed lower values in emotional diversity, spatial occupancy, and temporal occupancy compared to male characters in commercial films. Further, female characters were less likely to wear eyeglasses and also appeared more in static scenes, such as indoors.
Discrimination through Optimization
Authors: Ali Muhammad , Sapiezynski Piotr , Bogen Miranda , Korolova Aleksandra , Mislove Alan , Rieke Aaron
Published: November 2019

The enormous financial success of online advertising platforms is partially due to the precise targeting features they offer. Although researchers and journalists have found many ways that advertisers can target---or exclude---particular groups of users seeing their ads, comparatively little attention has been paid to the implications of the platform's ad delivery process, comprised of the platform's choices about which users see which ads. It has been hypothesized that this process can "skew" ad delivery in ways that the advertisers do not intend, making some users less likely than others to see particular ads based on their demographic characteristics. In this paper, we demonstrate that such skewed delivery occurs on Facebook, due to market and financial optimization effects as well as the platform's own predictions about the "relevance" of ads to different groups of users. We find that both the advertiser's budget and the content of the ad each significantly contribute to the skew of Facebook's ad delivery. Critically, we observe significant skew in delivery along gender and racial lines for "real" ads for employment and housing opportunities despite neutral targeting parameters. Our results demonstrate previously unknown mechanisms that can lead to potentially discriminatory ad delivery, even when advertisers set their targeting parameters to be highly inclusive. This underscores the need for policymakers and platforms to carefully consider the role of the ad delivery optimization run by ad platforms themselves---and not just the targeting choices of advertisers---in preventing discrimination in digital advertising.
Prefigurative Design as a Method for Research Justice
Authors: Asad Mariam
Published: November 2019

While there is growing concern around justice and equity, they mean different things in different socio-political and cultural contexts. Additionally, it can be difficult to make sense of how to incorporate the more abstract concept of justice into our research practices. This paper discusses prefigurative design as a framework for more just research practices to challenge inequity, particularly in community-based collaborations. I draw from past fieldwork with activist organizations and radical organizing literature to explore opportunities for how to engage with justice as academics, identifying three main opportunities for intervention through research: social relationships, resource distribution, and counter-institutions. I offer these contributions in the spirit of generative critique, in hopes that other researchers with similar concerns will iterate on these practices to commit to more just and equitable scholarly impacts.
The Effect of Expressive Biosignals on Empathy and Closeness for a Stigmatized Group Member
Authors: Liu Fannie , Kaufman Geoff , Dabbish Laura
Published: November 2019

We explore the potential for expressive biosignals, or displays of sensed physiological data as social cues, to influence perceptions of a member of a stigmatized group. In a between-subjects experiment (N=62) participants read a fictional interview with a drug addict in prison, and rated their empathy and closeness with the interviewee. Participants were randomly assigned to read either 1) the transcript of the interview by itself, 2) the transcript with a text description of the interviewee's heart rate, or 3) the transcript with a graph of the interviewee's heart rate. Results demonstrate that providing information about heart rate can increase empathy in terms of emotional perspective-taking. Additionally, visualizing the heart rate as a graph, as opposed to text, can increase closeness. We discuss the implications of these results and present suggestions for future directions.
Analyzing Wikipedia Deletion Debates with a Group Decision-Making Forecast Model
Authors: Mayfield Elijah , Black Alan W.
Published: November 2019

In this work we show that machine learning with natural language processing can accurately forecast the outcomes of group decision-making in online discussions. Specifically, we study Articles for Deletion, a Wikipedia forum for determining which content should be included on the site. Applying this model, we replicate several findings from prior work on the factors that predict debate outcomes; we then extend this prior work and present new avenues for study, particularly in the use of policy citation during discussion. Alongside these findings, we introduce a structured corpus and source code for analyzing over 400,000 deletion debates spanning Wikipedia's history, enabling future large-scale studies of group decision-making discourse
Human-AI Collaboration in Data Science
Authors: Wang Dakuo , Weisz Justin D. , Muller Michael , Ram Parikshit , Geyer Werner , Dugan Casey , Tausczik Yla , Samulowitz Horst , Gray Alexander
Published: November 2019

The rapid advancement of artificial intelligence (AI) is changing our lives in many ways. One application domain is data science. New techniques in automating the creation of AI, known as AutoAI or AutoML, aim to automate the work practices of data scientists. AutoAI systems are capable of autonomously ingesting and pre-processing data, engineering new features, and creating and scoring models based on a target objectives (e.g. accuracy or run-time efficiency). Though not yet widely adopted, we are interested in understanding how AutoAI will impact the practice of data science. We conducted interviews with 20 data scientists who work at a large, multinational technology company and practice data science in various business settings. Our goal is to understand their current work practices and how these practices might change with AutoAI. Reactions were mixed: while informants expressed concerns about the trend of automating their jobs, they also strongly felt it was inevitable. Despite these concerns, they remained optimistic about their future job security due to a view that the future of data science work will be a collaboration between humans and AI systems, in which both automation and human expertise are indispensable.
"Phantom Friend" or "Just a Box with Information"
Authors: Pradhan Alisha , Findlater Leah , Lazar Amanda
Published: November 2019

As voice-based conversational agents such as Amazon Alexa and Google Assistant move into our homes, researchers have studied the corresponding privacy implications, embeddedness in these complex social environments, and use by specific user groups. Yet it is unknown how users categorize these devices: are they thought of as just another object, like a toaster? As a social companion? Though past work hints to human-like attributes that are ported onto these devices, the anthropomorphization of voice assistants has not been studied in depth. Through a study deploying Amazon Echo Dot Devices in the homes of older adults, we provide a preliminary assessment of how individuals 1) perceive having social interactions with the voice agent, and 2) ontologically categorize the voice assistants. Our discussion contributes to an understanding of how well-developed theories of anthropomorphism apply to voice assistants, such as how the socioemotional context of the user (e.g., loneliness) drives increased anthropomorphism. We conclude with recommendations for designing voice assistants with the ontological category in mind, as well as implications for the design of technologies for social companionship for older adults.
"I Don't Want Them to Not Know"
Authors: Fernandez Julia R. , Birnholtz Jeremy
Published: November 2019

Dating platform research often focuses on people's decisions about when to reveal certain aspects of themselves to others, or self-disclosure. One example is deciding what to include in one's profile and what to reveal in chat conversations or in person. Transgender people face a particularly acute challenge in self-disclosure, but we know little about how they experience it on dating platforms. Revealing trans status can result in physical or emotional harm, but is also often considered necessary for a successful relationship and for self-fulfillment. To better understand disclosure of sensitive information, we interviewed 20 transgender dating platform users in the U.S. We find that direct, proactive disclosure of trans status was motivated by desires for safety and certainty, though this could involve tension. Physical separation and one-to-many communication surface as key affordances that facilitated disclosure. These results help us better understand motivations behind disclosure decisions.
The first fifty years of ACM SIGCOMM
Authors: Bonaventure Olivier
Published: November 2019

Network researchers know that packets are not always evenly spaced, they sometimes arrive in bursts. This burstiness is also present in history. Important events sometimes occur almost simultaneously even if there is no direct relationship between them. Fifty years ago, several historical events took place within a period of a few months. In July, after years of efforts, NASA engineers successfully launched Apollo 13 and the Eagle landed on the Moon. The first footsteps of Neil Armstrong and Buzz Aldrin have opened the era of space exploration and maybe another human will land on another planet during this century. One month later, hundreds of thousands of music fans gathered at the Woodstock festival. In parallel, a few computer scientists and engineers started to deploy prototype nodes of the ARPANET network. The first packets that they exchanged have initiated the revolution that brought the Internet and today's connected society. At that time, research in computer networks had already started and several members of this emerging community gathered in an interest group that later became ACM SIGCOMM.
Network protocol folklore
Authors: Radia Perlman
Published: November 2019

There's no way to understand today's networks without knowing the history. Too often, network protocols are taught as 'memorize the details of what is currently deployed', which creates a lot of confusion, and certainly does not encourage critical thinking. Some decisions have made today's networks unnecessarily complex and less functional. But surprisingly, mechanisms that were created out of necessity, to compensate for previous decisions, sometimes turn out to be useful for purposes other than the original reason they were invented. If the world had adopted a different approach originally, some very interesting technology may not have been invented. Given limited space in this article, we will not worry about exact details, but rather convey the main conceptual points, and only cover a few examples.
Reflections on "a control-theoretic approach to flow control"
Authors: Keshav S.
Published: November 2019

This article discusses the events that led to the publication of my paper 'A Control-Theoretic Approach to Flow Control' that won the Best Student Paper Award in 1991 and a Test-of-Time Award in 2007.
XORs in the past and future
Authors: Médard Muriel , Katti Sachin , Katabi Dina , Hu Wenjun , Rahul Hariharan , Crowcroft Jon
Published: November 2019

While placing the paper "XORs in the Air" in the context of the theoretical and practical understanding of network coding, we present a view of the progress of the field of network coding, In particular, we examine the interplay of theory and practice in the field.
ISSAC 2019 software presentations communicated by Yue Ren
Authors: Yao Shanshan , Feng Yifei , Jia Xiaohong , Shen Li-Yong
Published: November 2019

Implicit is a package for implicitizing rational planar curves and rational tensor product surfaces, developed on Maplesoft based on the state-of-the-art implicitization techniques. The main functions ImpCurve and ImpSurface return the implicit equation of a rational planar curve or a rational tensor product surface. Other popularly used functions, such as ImpDegree, ImpMatrix and ImpRuled that are used for deciding the implicit degree and the implicit matrix of a general rational surface, and computing the implicit equation of a rational ruled surface in a more efficient way, are also proposed.
SIAN
Authors: Hong Hoon , Ovchinnikov Alexey , Pogudin Gleb , Yap Chee
Published: November 2019

Many important real-world processes are modeled using systems of ordinary differential equations (ODEs) involving unknown parameters. The values of these parameters are usually inferred from experimental data. However, due to the structure of the model, there might be multiple parameter values that yield the same observed behavior even in the case of continuous noise-free data. It is important to detect such situations a priori, before collecting actual data. In this case, the only input is the model itself, so it is natural to tackle this question by methods of symbolic computation.

We present new software SIAN (Structural Identifiability ANalyser) that solves this problem. Our software allows to tackle problems that could not be tackled before. It is written in Maple and available at https://github.com/pogudingleb/SIAN.