bluuebunny/crossref_metadata_2025 huggingface dataset:
Acoustic texture rendering for extended sources in complex scenes
Authors: Zhang Zechen , Raghuvanshi Nikunj , Snyder John , Marschner Steve
Published: November 2019

Extended stochastic sources, like falling rain or a flowing waterway, provide an immersive ambience in virtual environments. In complex scenes, the rendered sound should vary naturally with listener position, differing not only in overall loudness but also in texture, to capture the indistinct murmur of a faraway brook versus the bright babbling of one up close. Modeling an ambient sound as a collection of random events such as individual raindrop impacts or water bubble oscillations, this variation can be seen as a change in the statistical distribution of events heard by the listener: the arrival rate of nearby, louder events relative to more distant or occluded, quieter ones. Reverberation and edge diffraction from scene geometry multiply and mix events more extensively compared to an empty scene and introduce salient spatial variation in texture. We formalize the notion of acoustic texture by introducing the
event loudness density
(ELD), which relates the rapidity of received events to their loudness. To model spatial variation in texture, the ELD is made a function of listener location in the scene. We show that this ELD field can be extracted from a single wave simulation for each extended source and rendered flexibly using a granular synthesis pipeline, with grains derived procedurally or from recordings. Our system yields believable, realtime changes in acoustic texture as the listener moves, driven by sound propagation in the scene.
Material-adapted refinable basis functions for elasticity simulation
Authors: Chen Jiong , Budninskiy Max , Owhadi Houman , Bao Hujun , Huang Jin , Desbrun Mathieu
Published: November 2019

In this paper, we introduce a hierarchical construction of material-adapted refinable basis functions and associated wavelets to offer efficient coarse-graining of linear elastic objects. While spectral methods rely on global basis functions to restrict the number of degrees of freedom, our basis functions are locally supported; yet, unlike typical polynomial basis functions, they are adapted to the material inhomogeneity of the elastic object to better capture its physical properties and behavior. In particular, they share spectral approximation properties with eigenfunctions, offering a good compromise between computational complexity and accuracy. Their construction involves only linear algebra and follows a fine-to-coarse approach, leading to a block-diagonalization of the stiffness matrix where each block corresponds to an intermediate scale space of the elastic object. Once this hierarchy has been precomputed, we can simulate an object at runtime on very coarse resolution grids and still capture the correct physical behavior, with orders of magnitude speedup compared to a fine simulation. We show on a variety of heterogeneous materials that our approach outperforms all previous coarse-graining methods for elasticity.
Blind image super-resolution with spatially variant degradations
Authors: Cornillère Victor , Djelouah Abdelaziz , Yifan Wang , Sorkine-Hornung Olga , Schroers Christopher
Published: November 2019

Existing deep learning approaches to single image super-resolution have achieved impressive results but mostly assume a setting with fixed pairs of high resolution and low resolution images. However, to robustly address realistic upscaling scenarios where the relation between high resolution and low resolution images is unknown, blind image super-resolution is required. To this end, we propose a solution that relies on three components: First, we use a degradation aware SR network to synthesize the HR image given a low resolution image and the corresponding blur kernel. Second, we train a kernel discriminator to analyze the generated high resolution image in order to predict errors present due to providing an incorrect blur kernel to the generator. Finally, we present an optimization procedure that is able to recover both the degradation kernel and the high resolution image by minimizing the error predicted by our kernel discriminator. We also show how to extend our approach to spatially variant degradations that typically arise in visual effects pipelines when compositing content from different sources and how to enable both local and global user interaction in the upscaling process.
Selectively metropolised Monte Carlo light transport simulation
Authors: Bitterli Benedikt , Jarosz Wojciech
Published: November 2019

Light transport is a complex problem with many solutions. Practitioners are now faced with the difficult task of choosing which rendering algorithm to use for any given scene. Simple Monte Carlo methods, such as path tracing, work well for the majority of lighting scenarios, but introduce excessive variance when they encounter transport they cannot sample (such as caustics). More sophisticated rendering algorithms, such as bidirectional path tracing, handle a larger class of light transport robustly, but have a high computational overhead that makes them inefficient for scenes that are not dominated by difficult transport. The underlying problem is that rendering algorithms can only be executed indiscriminately on all transport, even though they may only offer improvement for a subset of paths. In this paper, we introduce a new scheme for selectively combining different Monte Carlo rendering algorithms. We use a simple transport method (e.g. path tracing) as the base, and treat high variance "fireflies" as seeds for a Markov chain that locally uses a Metropolised version of a more sophisticated transport method for exploration, removing the firefly in an unbiased manner. We use a weighting scheme inspired by multiple importance sampling to partition the integrand into regions the base method can sample well and those it cannot, and only use Metropolis for the latter. This constrains the Markov chain to paths where it offers improvement, and keeps it away from regions already handled well by the base estimator. Combined with stratified initialization, short chain lengths and careful allocation of samples, this vastly reduces non-uniform noise and temporal flickering artifacts normally encountered with a global application of Metropolis methods. Through careful design choices, we ensure our algorithm never performs much worse than the base estimator alone, and usually performs significantly better, thereby reducing the need to experiment with different algorithms for each scene.
Crowdsourcing Perceptions of Fair Predictors for Machine Learning
Authors: van Berkel Niels , Goncalves Jorge , Hettiachchi Danula , Wijenayake Senuri , Kelly Ryan M. , Kostakos Vassilis
Published: November 2019

The increased reliance on algorithmic decision-making in socially impactful processes has intensified the calls for algorithms that are unbiased and procedurally fair. Identifying fair predictors is an essential step in the construction of equitable algorithms, but the lack of ground-truth in fair predictor selection makes this a challenging task. In our study, we recruit 90 crowdworkers to judge the inclusion of various predictors for recidivism. We divide participants across three conditions with varying group composition. Our results show that participants were able to make informed decisions on predictor selection. We find that agreement with the majority vote is higher when participants are part of a more diverse group. The presented workflow, which provides a scalable and practical approach to reach a diverse audience, allows researchers to capture participants' perceptions of fairness in private while simultaneously allowing for structured participant discussion.
Implications of Grassroots Sustainable Agriculture Community Values on the Design of Information Systems
Authors: Norton Juliet , Penzenstadler Birgit , Tomlinson Bill
Published: November 2019

Information system designers embed values into the systems they design, even if unwittingly. However, the values embedded in many information systems clash with values held by many sustainability communities. This research focuses on two grassroots sustainable agriculture communities, which are seeking to develop a food infrastructure that is under their own control, and thereby more resilient to disruptions across the globe. This paper presents a five-year ethnographic study of these two communities, maps out the values of members of these communities, and explores the implications of their values on the information systems that members use and that could be developed to support them in the future. By doing so, we hope to influence the design of future information systems to align more closely with the values of these stakeholders, and through these stakeholders to move toward a food system that supports food security and global sustainability.
Collaborative Data Work Towards a Caring Democracy
Authors: Meng Amanda , DiSalvo Carl , Zegura Ellen
Published: November 2019

Researchers in human-centered computing have surfaced a feminist ethic of care in interaction with technologies, in data collection, and in data work. Drawing on two years of ethnographic fieldwork, we consider how democratic caring might be enacted and sustained through collaborative data work. We employ philosopher Joan Tronto's theory of caring democracy to structure our analysis of a resident-led initiative that uses data to organize and address issues of neglect and abandonment in their neighborhood. Adding to the CSCW literature on sociotechnical systems of care, we look particularly at Tronto's concept of caring democracy where caring needs and the ways in which they are met are an ongoing and inclusive process of assigning and reassigning caring responsibilities, characterized by both equality of voice and freedom from domination. This work develops grounded insight into the practice of democratic caring and how collaborative data work is relevant to this caring practice. We discuss opportunities and challenges for a data-supported caring democracy and address how caring democracy technologies are different from other modern civic technology practices. We conclude with a call to researchers to identify and enact democratic caring experiments in the small.
Information Materialities of Citizen Communication in the U.S. Congress
Authors: McDonald Samantha , Mazmanian Melissa
Published: November 2019

In this paper, we use a materiality lens to explore how information and communication technologies condition interaction between citizens and policymakers of the U.S. Congress. We work with ethnographic data - six months of observation in Washington D.C. and 48 interviews with staff in the House of Representatives. Customer relation management systems (CRMs) used by Congress are one of numerous technologies expected to enhance responsive communication between citizens and representatives. We find, instead, that these technologies promote the datafication of citizen information that configures and constrains how policymakers engage citizens as legitimate actors within the policy-making process. CRMs not only mediate communication between citizens and policymakers, they shape the idea of what communication between citizens and policymakers can be and how citizens are viewed in the eyes of policymakers and their staff. Thus, we extend our understanding of the ways in which material configurations of communication technologies influence not only how communication acts unfolds, but also how each partner conceives of and engages with the other. This has dramatic implications for the possibilities of digital communication channels to enhance, or uphold, the ideals of a representative democracy.
Higher Education Check-Ins
Authors: Huang Yun , Sang Yisi , Wu Qunfang , Yao Yaxing
Published: November 2019

A large body of literature is dedicated to understanding people's check-in behavior when they use location sharing services to pair their location with a venue, e.g., a restaurant, a park, etc. Check-in behavior in higher education settings, e.g., where students and instructors have academic purposes for check-ins, is under-studied. In this work, we explore how university students apply two different mechanisms, i.e., automatic and manual location-sharing services, to conduct check-ins for an academic purpose (i.e., students sharing their class attendance with their instructor). More specifically, a Bluetooth Low Energy beacon-based technology is applied to enable automatic class check-ins. We conducted two field trials with a total of 141 university students. Our findings showed that several social, technological, and psychological factors impacted the use of auto and manual check-ins. Feedback from the student participants suggested that future higher education check-in systems may need to consider the integration of check-ins for a variety of purposes.
"Am I Never Going to Be Free of All This Crap?"
Authors: Pinter Anthony T. , Jiang Jialun Aaron , Gach Katie Z. , Sidwell Melanie M. , Dykes James E. , Brubaker Jed R.
Published: November 2019

Every day on social media, people see streams of content curated by algorithms that leverage their relationships, preferences, and identities. However, algorithms can oversimplify the complexity of people's social contexts. Consequently, algorithms can present content to people in ways that are insensitive to their circumstances. Through 19 in-depth interviews, our empirical study examines instances of contextually insensitive content through the lens of people's upsetting encounters with content about their ex-romantic partners on Facebook. We characterize the encounters our participants had with content about their exes, including where on Facebook it occurred, the types of social connections involved in the content, and participants' perceptions of why the content appeared. Based on our findings, we describe the "social periphery"---the complex social networks and data that enable inferred connections around otherwise explicit relationships---and discuss the design challenges that the periphery presents designers.
Understanding Expert Disagreement in Medical Data Analysis through Structured Adjudication
Authors: Schaekermann Mike , Beaton Graeme , Habib Minahz , Lim Andrew , Larson Kate , Law Edith
Published: November 2019

Expert disagreement is pervasive in clinical decision making and collective adjudication is a useful approach for resolving divergent assessments. Prior work shows that expert disagreement can arise due to diverse factors including expert background, the quality and presentation of data, and guideline clarity. In this work, we study how these factors predict initial discrepancies in the context of medical time series analysis, examining why certain disagreements persist after adjudication, and how adjudication impacts clinical decisions. Results from a case study with 36 experts and 4,543 adjudicated cases in a sleep stage classification task show that these factors contribute to both initial disagreement and resolvability, each in their own unique way. We provide evidence suggesting that structured adjudication can lead to significant revisions in treatment-relevant clinical parameters. Our work demonstrates how structured adjudication can support consensus and facilitate a deep understanding of expert disagreement in medical data analysis.
All Users are (Not) Created Equal
Authors: Baumer Eric P. S. , Guha Shion , Skeba Patrick , Gay Geraldine
Published: November 2019

Relatively little work has empirically examined use and non-use of social technologies as more than a dichotomous binary, despite increasing calls to do so. This paper compares three different forms of non/use that might otherwise fall under the single umbrella of Facebook "user": (1) those who have a current active account; (2) those who have deactivated their account; and (3) those who have considered deactivating but not actually done so. A subset of respondents (N=256) from a larger, demographically representative sample of internet users completed measures for usage and perceptions of Facebook, Facebook addiction, privacy experiences and behaviors, and demographics. Multinomial logistic regression modeling shows four specific variables as most predictive of a respondent's type: negative effects from "addictive" use, subjective intensity of Facebook usage, number of Facebook friends, and familiarity with or use of Facebook's privacy settings. These findings both fill gaps left by, and help resolve conflicting expectations from, prior work. Furthermore, they demonstrate how valuable insights can be gained by disaggregating "users" based on different forms of engagement with a given technology.
Normal and Easy
Authors: Song Yunpeng , Faklaris Cori , Cai Zhongmin , Hong Jason I. , Dabbish Laura
Published: November 2019

Work is being digitized across all sectors, and digital account sharing has become common in the workplace. In this paper, we conduct a qualitative and quantitative study of digital account sharing practices in the workplace. Across two surveys, we examine the sharing process at work, probing what accounts people share, how and why they share those accounts, and identifying the major challenges people face in sharing accounts. Our results demonstrate that account sharing in the modern workplace serves as a norm rather than a simple workaround; centralizing collaborative activity and reducing boundary management effort are key motivations for sharing. But people still struggle with a lack of activity accountability and awareness, conflicts over simultaneous access, difficulties controlling access, and collaborative password use. Our work provides insights into the current difficulties people face in workplace collaboration with online account sharing, as a result of inappropriate designs that still assume a single-user model for accounts. We highlight opportunities for CSCW and HCI researchers and designers to better support sharing by multiple people in a more usable and secure way.
Narrative Paths and Negotiation of Power in Birth Stories
Authors: Antoniak Maria , Mimno David , Levy Karen
Published: November 2019

Birth stories have become increasingly common on the internet, but they have received little attention as a computational dataset. These unsolicited, publicly posted stories provide rich descriptions of decisions, emotions, and relationships during a common but sometimes traumatic medical experience. These personal details can be illuminating for medical practitioners, and due to their shared structures, birth stories are also an ideal testing ground for narrative analysis techniques. We present an analysis of 2,847 birth stories from an online forum and demonstrate the utility of these stories for computational work. We discover clear sentiment, topic and persona-based patterns that both model the expected narrative event sequences of birth stories and highlight diverging pathways and exceptions to narrative norms. The authors' motivation to publicly post these personal stories can be a way to regain power after a surveilled and disempowering experience, and we explore power relationships between the personas in the stories, showing that these dynamics can vary with the type of birth (e.g., medicated vs unmedicated). Finally, birth stories exist in a space that is both public and deeply personal. This liminality poses a challenge for analysis and presentation, and we discuss tradeoffs and ethical practices for this collection. WARNING: This paper includes detailed narratives of pregnancy and birth.
MyAutsomeFamilyLife
Authors: Borgos-Rodriguez Katya , Ringland Kathryn E. , Piper Anne Marie
Published: November 2019

While parents of young children regularly make decisions about sharing content about their child or family online, we know less about how they create, produce, and share video-based content of children with stigmatizing experiences. Through an analysis of publicly available content on YouTube, supplemented with semi-structured interviews, we report on the ways in which parents of children with developmental disabilities produce, share, and interact with others through videos of their children's experiences. Our analysis finds that parents disclose child information on YouTube to build authenticity, connect with others, advocate for social change, and justify monetization and child involvement. We discuss tensions between parents' practices and the ethical complexities of sharing and studying parent-generated content featuring children with disabilities.
Precarious Interventions
Authors: Kaziunas Elizabeth , Klinkman Michael S. , Ackerman Mark S.
Published: November 2019

In this paper, we present ethnographic account of people's everyday behavioral health experiences in the city of Jackson, Michigan to explore community forms of care work through an infrastructural lens. Detailing people's interactions with clinical processes and health policies, local resources, and diverse social worlds, we highlight problematic healthcare delivery gaps, as well as the informal (and often invisible) practices people depend upon to manage their health needs given socioeconomic hardships and cultural concerns. We also discuss the city's efforts to support local behavioral health needs through the development of a community health record. Placing fieldwork findings in conversation with the goals of this ongoing civic design project, we propose the analytic sensibility of precarious intervention to unpack the significance of the infrastructural tensions and power relations at play when people seek solutions to complex sociotechnical problems. Precarious intervention calls for CSCW research that attends to 1) the collective labor necessary to create and maintain ecologies of care in the face of infrastructural brokenness; and 2) the high-stakes and varied costs of 'engagement' for different community stakeholders.
This Thing Called Fairness
Authors: Mulligan Deirdre K. , Kroll Joshua A. , Kohli Nitin , Wong Richmond Y.
Published: November 2019

The explosion in the use of software in important sociotechnical systems has renewed focus on the study of the way technical constructs reflect policies, norms, and human values. This effort requires the engagement of scholars and practitioners from many disciplines. And yet, these disciplines often conceptualize the operative values very differently while referring to them using the same vocabulary. The resulting conflation of ideas confuses discussions about values in technology at disciplinary boundaries. In the service of improving this situation, this paper examines the value of shared vocabularies, analytics, and other tools that facilitate conversations about values in light of these disciplinary specific conceptualizations, the role such tools play in furthering research and practice, outlines different conceptions of "fairness" deployed in discussions about computer systems, and provides an analytic tool for interdisciplinary discussions and collaborations around the concept of fairness. We use a case study of risk assessments in criminal justice applications to both motivate our effort--describing how conflation of different concepts under the banner of "fairness" led to unproductive confusion--and illustrate the value of the fairness analytic by demonstrating how the rigorous analysis it enables can assist in identifying key areas of theoretical, political, and practical misunderstanding or disagreement, and where desired support alignment or collaboration in the absence of consensus.
LEAP
Authors: Yadav Deepika , Bhandari Anushka , Singh Pushpendra
Published: November 2019

Despite a crucial role in providing public health services, Community Health Workers (CHWs) remain disadvantaged in receiving effective skill-building opportunities. Due to the lack of health experts and appropriate infrastructure, it becomes challenging to provide training on a regular basis. Our aim is to investigate opportunities for designing technology-supported collaborative learning to compensate for the limited availability of instructors. We designed a mobile learning-based peer-led educational intervention, and conducted an eight week long between-group study with 120 CHWs across four districts of Delhi, India. We found that CHWs were able to participate and use the system on their own leading to significant knowledge gains and increased desire to learn. With little guidance, CHWs exhibited benefits of collaborative learning in terms of positive interdependence on each other and use of interpersonal skills. The informal peer learning environment encouraged CHWs to have discourses on deeper societal aspects e.g. their role in society.
Increasing Native Speakers' Awareness of the Need to Slow Down in Multilingual Conversations Using a Real-Time Speech Speedometer
Authors: Duan Wen , Yamashita Naomi , Fussell Susan R.
Published: November 2019

Collaborating using a common language can be challenging for non-native speakers (NNS). These challenges can be reduced when native speakers (NS) adjust their speech behavior for NNS, for example by speaking more slowly. In this study, we examined whether the use of real-time speech rate feedback (a speech speedometer) would help NS monitor their speaking speed and adjust for NNS accordingly. We conducted a laboratory experiment with 20 triads of 2 NS and 1 NNS. NS in half of the groups were given the speech speedometer. We found that NS with the speech speedometer were significantly more motivated to slow down their speech but they did not actually speak more slowly, although they made other speech adjustments. Furthermore, NNS perceived the speech of NS with the speedometer less clear, and they felt less accommodated. The results highlight the need for tools that create scaffolding to help NS make speech accommodations. We conclude with some design ideas for these scaffolding tools.
Human Decision Making with Machine Assistance
Authors: Grgić-Hlača Nina , Engel Christoph , Gummadi Krishna P.
Published: November 2019

Much of political debate focuses on the concern that machines might take over. Yet in many domains it is much more plausible that the ultimate choice and responsibility remain with a human decision-maker, but that she is provided with machine advice. A quintessential illustration is the decision of a judge to bail or jail a defendant. In multiple jurisdictions in the US, judges have access to a machine prediction about a defendant's recidivism risk. In our study, we explore how receiving machine advice influences people's bail decisions. We run a vignette experiment with laypersons whom we test on a subsample of cases from the database of this prediction tool. In study 1, we ask them to predict whether defendants will recidivate before tried, and manipulate whether they have access to machine advice. We find that receiving machine advice has a small effect, which is biased in the direction of predicting no recidivism. In the field, human decision makers sometimes have a chance, after the fact, to learn whether the machine has given good advice. In study 2, after each trial we inform participants of ground truth. This does not make it more likely that they follow the advice, despite the fact that the machine is (on average) slightly more accurate than real judges. This also holds if initially the advice is mostly correct, or if it initially is mostly to predict (no) recidivism. Real judges know that their decisions affect defendants' lives. They may also be concerned about reelection or promotion. Hence a lot is at stake. In study 3 we emulate high stakes by giving participants a financial incentive. An incentive to find the ground truth, or to avoid false positive or false negatives, does not make participants more sensitive to machine advice. But an incentive to follow the advice is effective.
The Work of Bilingual Parent-Education Liaisons
Authors: Wong-Villacres Marisol , Kumar Neha , DiSalvo Betsy
Published: November 2019

In this paper, we examine the information work that bilingual parent-education liaisons perform to create connections towards assisting immigrant parents in the United States. As part of formal and informal educational institutions, liaisons operate between different social worlds---within and beyond the domain of education---to maximize immigrant parents' engagement in their children's academic lives. Drawing upon ethnographic fieldwork with low-income Latino immigrants and their liaisons, we explore how liaisons leverage technology, content, and people to align these worlds; bringing them closer to mutual understanding. We borrow inspiration from the analytical lens of seams suggested by Vertesi to explore how liaisons manage the "seams'' between worlds. This analysis provides a rich and unique perspective of the work that successfully engages immigrant parents with their children's education, as well as the tensions that challenge that engagement. This understanding of the work that liaisons do with and across seams provides insights to inform design directions for technology that could facilitate and amplify their efforts. Finally, we highlight how exploring the seams that liaisons work with can inform the field of Computer-Supported Collaborative Work (CSCW) on the role of technology in mediation.
"It doesn't win you friends"
Authors: Das Maitraye , Gergle Darren , Piper Anne Marie
Published: November 2019

Collaborative writing tools have become ubiquitous in today's world and are used widely in many professional organizations and academic settings. Yet, we know little about how ability-diverse teams, such as those involving people with and without vision impairments, make use of collaborative writing tools. We report on interviews with 20 academics and professionals who are blind or visually impaired and perform collaborative writing with sighted colleagues. Our findings reveal that people with vision impairments perform collaborative writing activities through four interconnected processes, which include learning an ecosystem of (in)accessible tools, adapting to complexities of collaborative features, balancing the cost and benefit of accessibility, and navigating power dynamics within organizations. We discuss how our analysis contributes to theories of accessibility in collaboration and offers practical insights for future collaborative system design.
Deconstructing Creativity
Authors: Hsueh Stacy , Alaoui Sarah Fdili , Mackay Wendy E.
Published: November 2019

The stereotype of creativity as an isolated, individual activity has given way to a more nuanced understanding of creativity as a social process. Our interview study of 23 contemporary music composers and choreographers focuses on the role that artifacts play in shaping creative collaborations with performers. We found that creators and performers form relationships where the creator acts as an author, a curator, a planner, or a researcher, and the performer acts as an interpreter, a creator, an improvisor, or an informant. Furthermore, we found that creators sculpt, layer, remix artifacts, moving fluidly across these different forms of interaction throughout the creative process. We conclude that the slippages that occur at the seams between roles and interactions drive creativity forward by opening up pathways into the future.
Did It Have To End This Way?
Authors: Whiting Mark E. , Blaising Allie , Barreau Chloe , Fiuza Laura , Marda Nik , Valentine Melissa , Bernstein Michael S.
Published: November 2019

Was a problematic team always doomed to frustration, or could it have ended another way? In this paper, we study the consistency of team fracture: a loss of team viability so severe that the team no longer wants to work together. Understanding whether team fracture is driven by the membership of the team, or by how their collaboration unfolded, motivates the design of interventions that either identify compatible teammates or ensure effective early interactions. We introduce an online experiment that reconvenes the same team without members realizing that they have worked together before, enabling us to temporarily erase previous team dynamics. Participants in our study completed a series of tasks across multiple teams, including one reconvened team, and privately blacklisted any teams that they would not want to work with again. We identify fractured teams as those blacklisted by half the members. We find that reconvened teams are strikingly polarized by task in the consistency of their fracture outcomes. On a creative task, teams might as well have been a completely different set of people: the same teams changed their fracture outcomes at a random chance rate. On a cognitive conflict and on an intellective task, the team instead replayed the same dynamics without realizing it, rarely changing their fracture outcomes. These results indicate that, for some tasks, team fracture can be strongly influenced by interactions in the first moments of a team's collaboration, and that interventions targeting these initial moments may be critical to scaffolding long-lasting teams.
The Roles Bots Play in Wikipedia
Authors: Zheng Lei (Nico) , Albano Christopher M. , Vora Neev M. , Mai Feng , Nickerson Jeffrey V.
Published: November 2019

Bots are playing an increasingly important role in the creation of knowledge in Wikipedia. In many cases, editors and bots form tightly knit teams. Humans develop bots, argue for their approval, and maintain them, performing tasks such as monitoring activity, merging similar bots, splitting complex bots, and turning off malfunctioning bots. Yet this is not the entire picture. Bots are designed to perform certain functions and can acquire new functionality over time. They play particular roles in the editing process. Understanding these roles is an important step towards understanding the ecosystem, and designing better bots and interfaces between bots and humans. This is important for understanding Wikipedia along with other kinds of work in which autonomous machines affect tasks performed by humans. In this study, we use unsupervised learning to build a nine category taxonomy of bots based on their functions in English Wikipedia. We then build a multi-class classifier to classify 1,601 bots based on labeled data. We discuss different bot activities, including their edit frequency, their working spaces, and their software evolution. We use a model to investigate how bots playing certain roles will have differential effects on human editors. In particular, we build on previous research on newcomers by studying the relationship between the roles bots play, the interactions they have with newcomers, and the ensuing survival rate of the newcomers.
How Teachers in India Reconfigure their Work Practices around a Teacher-Oriented Technology Intervention
Authors: Varanasi Rama Adithya , Kizilcec René F. , Dell Nicola
Published: November 2019

The proliferation of mobile devices around the world, combined with falling costs of hardware and Internet connectivity, have resulted in an increasing number of organizations that work to introduce educational technology interventions into low-income schools in the Global South. However, to date, most prior HCI research examining such interventions has focused on interventions that target students. In this paper, we expand prior literature by examining an intervention, called Meghshala, that targets teachers in low-income schools as its primary users. Through interviews and observations with 39 participants from 12 government schools in India, we show how the introduction of a teacher-focused technology intervention causes teachers to reconfigure their work practices, including lesson preparation, in-classroom teaching practices, bureaucratic work processes, and post-teaching feedback mechanisms. We use the concept of material agency to analyze our findings with respect to teacher agency and reconfiguration, and use theories of teacher knowledge to highlight the kinds of knowledge production that teachers in our research context tend to focus on (e.g., content knowledge). Finally, we offer design opportunities for future teacher-focused technology interventions.
The Rise and Fall of the Note
Authors: Geiger R Stuart
Published: November 2019

In this note, I quantitatively examine various trends in the lengths of published papers in ACM CSCW from 2000-2018, focusing on several major transitions in editorial and reviewing policy. The focus is on the rise and fall of the 4-page note, which was introduced in 2004 as a separate submission type to the 10-page double-column "full paper" format. From 2004-2012, 4-page notes of 2,500 to 4,500 words consistently represented about 20-35% of all publications. In 2013, minimum and maximum page lengths were officially removed, with no formal distinction made between full papers and notes. The note soon completely disappeared as a distinct genre, which co-occurred with a trend in steadily rising paper lengths. I discuss such findings both as they directly relate to local concerns in CSCW and in the context of longstanding theoretical discussions around genre theory and how socio-technical structures and affordances impact participation in distributed, computer-mediated organizations and user-generated content platforms. There are many possible explanations for the decline of the note and the emergence of longer and longer papers, which I identify for future work. I conclude by addressing the implications of such findings for the CSCW community, particularly given how genre norms impact what kinds of scholarship and scholars thrive in CSCW, as well as whether new top-down rules or bottom-up guidelines ought to be developed around paper lengths and different kinds of contributions.
Pen-and-paper Rituals in Service Interaction
Authors: Dolata Mateusz , Agotai Doris , Schubiger Simon , Schwabe Gerhard
Published: November 2019

Advisory services are ritualized encounters between an expert and an advisee. Empathetic, high-touch relationship between those two parties was identified as the key aspect of a successful advisory encounter. To facilitate the high-touch interaction, advisors established rituals which stress the unique, individual character of each client and each single encounter. Simultaneously, organizations like banks or insurances rolled out tools and technologies for use in advisory services to offer a uniform experience and consistent quality across branches and advisors. As a consequence, advisors were caught between the high-touch and high-tech aspects of an advisory service. This manuscript presents a system that accommodates for high-touch rituals and practices and combines them with high-tech collaboration. The proposed solution augments pen-and-paper practices with digital content and affords new material performances coherent with the existing rituals. The evaluation in realistic mortgage advisory services unveils the potential of mixed reality approaches for application in professional, institutional settings. The blow-by-blow analysis of the conversations reveals how an advisory service can become equally high-tech and high-touch thanks to a careful ritual-oriented system design. As a consequence, this paper presents a solution to the tension between the high-touch and high-tech tendencies in advisory services.
The Language of LGBTQ+ Minority Stress Experiences on Social Media
Authors: Saha Koustuv , Kim Sang Chan , Reddy Manikanta D. , Carter Albert J. , Sharma Eva , Haimson Oliver L. , De Choudhury Munmun
Published: November 2019

LGBTQ+ (lesbian, gay, bisexual, transgender, queer) individuals are at significantly higher risk for mental health challenges than the general population. Social media and online communities provide avenues for LGBTQ+ individuals to have safe, candid, semi-anonymous discussions about their struggles and experiences. We study minority stress through the language of disclosures and self-experiences on the r/lgbt Reddit community. Drawing on Meyer's minority stress theory, and adopting a combined qualitative and computational approach, we make three primary contributions, 1) a theoretically grounded codebook to identify minority stressors across three types of minority stress-prejudice events, perceived stigma, and internalized LGBTphobia, 2) a machine learning classifier to scalably identify social media posts describing minority stress experiences, that achieves an AUC of 0.80, and 3) a lexicon of linguistic markers, along with their contextualization in the minority stress theory. Our results bear implications to influence public health policy and contribute to improving knowledge relating to the mental health disparities of LGBTQ+ populations. We also discuss the potential of our approach to enable designing online tools sensitive to the needs of LGBTQ+ individuals.
Never waste a mid-life crisis
Authors: Rexford Jennifer
Published: November 2019

Creating a better Internet---a global communications infrastructure that is more secure, reliable, performant, flexible, and so on---is one of the grand challenges of our time. Yet, making substantive change to such a large, distributed, operational network is inherently difficult. This position paper argues that the networking research community should come together and adopt a sort of "ambitious pragmatism" that tackles the big problems while identifying the practical steps to take along the way. The community can work together to (i) identify and precisely formulate the main problems we need to address, (ii) more deeply understand a diverse array of practical constraints (including business drivers, economic incentives, government policies, and more), and (iii) create new deployment platforms and institutional structures to enable good research ideas to "cross the chasm" to deployment.
Reflections on SIGCOMM's fiftieth anniversary
Authors: Davie Bruce
Published: November 2019

On the occasion of the fiftieth anniversary of SIGCOMM, this article contains the reflections of a past SIGCOMM chair on the field of networking over the past few decades.
Reflections on being SIGCOMM chair 2013--2017
Authors: Keshav S.
Published: November 2019

This article discusses my personal view of being Chair of SIGCOMM from 2013 to 2017.
Reflections on being CCR editor 2008--2012
Authors: Keshav S.
Published: November 2019

This article discusses my personal view of being Editor of CCR from 2008 to 2012.
Retrospective on "towards an active network architecture"
Authors: Wetherall David , Tennenhouse David
Published: November 2019

Network programmability has metamorphosed over the past twenty years from the controversial research vision of active networks, through PlanetLab, to the juggernaut of SDN and OpenFlow that has swept industry. Now PISA switches are emerging with support for protocol-independent reconfigurability. We reflect on how network architecture has evolved along a different path than we had foreseen to arrive at a place that is not so different than we and other researchers had hoped and imagined.
From ethane to SDN and beyond
Authors: Casado Martín , McKeown Nick , Shenker Scott
Published: November 2019

We briefly describe the history behind the Ethane paper and its ultimate evolution into SDN and beyond.
Implicit Leadership Theories, Implicit Followership Theories, and Dynamic Processing of Leadership Information
Authors: Lord Robert G. , Epitropaki Olga , Foti Roseanne J. , Hansbrough Tiffany Keller
Published: November 2019

We offer a comprehensive review of the theoretical underpinnings and existing empirical evidence in the implicit leadership and implicit followership theories domain. After briefly touching on the historical roots of information-processing approaches to leadership and leader categorization theory, we focus on current contextualized and dynamic perspectives. We specifically present neural network approaches and adaptive resonance processes that guide leadership perceptions. We further address measurement issues, emerging areas of study such as implicit leadership theories, and identity and cross-cultural issues. We offer specific avenues for future research in the form of a systematic list of unanswered research questions and further outline leadership development implications.
Marrow Adipocytes: Origin, Structure, and Function
Authors: de Paula Francisco J.A. , Rosen Clifford J.
Published: November 2019

The skeleton harbors an array of lineage cells that have an essential role in whole body homeostasis. Adipocytes start the colonization of marrow space early in postnatal life, expanding progressively and influencing other components of the bone marrow through paracrine signaling. In this unique, closed, and hypoxic environment close to the endosteal surface and adjacent to the microvascular space the marrow adipocyte can store or provide energy, secrete adipokines, and target neighboring bone cells. Adipocyte progenitors can also migrate from the bone marrow to populate white adipose tissue, a process that accelerates during weight gain. The marrow adipocyte also has an endocrine role in whole body homeostasis through its varied secretome that targets distant adipose depots, skeletal muscle, and the nervous system. Further insights into the biology of this unique and versatile cell will undoubtedly lead to novel therapeutic approaches to metabolic and age-related disorders such as osteoporosis and diabetes mellitus.
Representation Learning: A Statistical Perspective
Authors: Xie Jianwen , Gao Ruiqi , Nijkamp Erik , Zhu Song-Chun , Wu Ying Nian
Published: November 2019

Learning representations of data is an important problem in statistics and machine learning. While the origin of learning representations can be traced back to factor analysis and multidimensional scaling in statistics, it has become a central theme in deep learning with important applications in computer vision and computational neuroscience. In this article, we review recent advances in learning representations from a statistical perspective. In particular, we review the following two themes: ( a) unsupervised learning of vector representations and ( b) learning of both vector and matrix representations.
Disentangling the Gordian knot of local metabolic control of coronary blood flow
Authors: Tune Johnathan D. , Goodwill Adam G. , Kiel Alexander M. , Baker Hana E. , Bender Shawn B. , Merkus Daphne , Duncker Dirk J.
Published: November 2019

Recognition that coronary blood flow is tightly coupled with myocardial metabolism has been appreciated for well over half a century. However, exactly how coronary microvascular resistance is tightly coupled with myocardial oxygen consumption (MV̇o2) remains one of the most highly contested mysteries of the coronary circulation to this day. Understanding the mechanisms responsible for local metabolic control of coronary blood flow has been confounded by continued debate regarding both anticipated experimental outcomes and data interpretation. For a number of years, coronary venous Po2 has been generally accepted as a measure of myocardial tissue oxygenation and thus the classically proposed error signal for the generation of vasodilator metabolites in the heart. However, interpretation of changes in coronary venous Po2 relative to MV̇o2 are quite nuanced, inherently circular in nature, and subject to confounding influences that remain largely unaccounted for. The purpose of this review is to highlight difficulties in interpreting the complex interrelationship between key coronary outcome variables and the arguments that emerge from prior studies performed during exercise, hemodilution, hypoxemia, and alterations in perfusion pressure. Furthermore, potential paths forward are proposed to help to facilitate further dialogue and study to ultimately unravel what has become the Gordian knot of the coronary circulation.