bluuebunny/crossref_metadata_2025 huggingface dataset:
DeepFovea
Authors: Kaplanyan Anton S. , Sochenov Anton , Leimkühler Thomas , Okunev Mikhail , Goodall Todd , Rufo Gizem
Published: November 2019

In order to provide an immersive visual experience, modern displays require head mounting, high image resolution, low latency, as well as high refresh rate. This poses a challenging computational problem. On the other hand, the human visual system can consume only a tiny fraction of this video stream due to the drastic acuity loss in the peripheral vision. Foveated rendering and compression can save computations by reducing the image quality in the peripheral vision. However, this can cause noticeable artifacts in the periphery, or, if done conservatively, would provide only modest savings. In this work, we explore a novel foveated reconstruction method that employs the recent advances in generative adversarial neural networks. We reconstruct a plausible peripheral video from a small fraction of pixels provided every frame. The reconstruction is done by finding the closest matching video to this sparse input stream of pixels on the learned manifold of natural videos. Our method is more efficient than the state-of-the-art foveated rendering, while providing the visual experience with no noticeable quality degradation. We conducted a user study to validate our reconstruction method and compare it against existing foveated rendering and video compression techniques. Our method is fast enough to drive gaze-contingent head-mounted displays in real time on modern hardware. We plan to publish the trained network to establish a new quality bar for foveated rendering and compression as well as encourage follow-up research.
Deep point correlation design
Authors: Leimkühler Thomas , Singh Gurprit , Myszkowski Karol , Seidel Hans-Peter , Ritschel Tobias
Published: November 2019

Designing point patterns with desired properties can require substantial effort, both in hand-crafting coding and mathematical derivation. Retaining these properties in multiple dimensions or for a substantial number of points can be challenging and computationally expensive. Tackling those two issues, we suggest to automatically generate scalable point patterns from design goals using deep learning. We phrase pattern generation as a deep composition of weighted distance-based unstructured filters. Deep point pattern design means to optimize over the space of all such compositions according to a user-provided
point correlation loss
, a small program which measures a pattern's fidelity in respect to its spatial or spectral statistics, linear or non-linear (e. g., radial) projections, or any arbitrary combination thereof. Our analysis shows that we can emulate a large set of existing patterns (blue, green, step, projective, stair, etc.-noise), generalize them to countless new combinations in a systematic way and leverage existing error estimation formulations to generate novel point patterns for a user-provided class of integrand functions. Our point patterns scale favorably to multiple dimensions and numbers of points: we demonstrate nearly 10k points in 10-D produced in one second on one GPU. All the resources (source code and the pre-trained networks) can be found at https://sampling.mpi-inf.mpg.de/deepsampling.html.
Orienting to Networked Grief
Authors: Brubaker Jed R. , Hayes Gillian R. , Mazmanian Melissa
Published: November 2019

Contemporary American experiences of death and mourning increasingly extend onto social network sites, where friends gather to memorialize the deceased. That "everyone grieves in their own way'' may be true, but it forecloses important questions about how people evaluate these expressions, their relationship to others who are grieving, and impacts on their own experiences of grief. Drawing from mixed-methods research conducted over five years, we describe how individuals position themselves within and evaluate expressions of networked grief. We start by identifying five orientations -- reinforcing, supporting, transferring, objecting, and isolating -- that describe how individuals evaluate actions of grievers, position themselves relative to the network, and act when they encounter grief. We then describe factors and tensions that influence how individuals arrive at these orientations. Based on our findings, we argue that the design of social media can be sensitized to diverse needs by adopting a situated perspective within a dynamic post-mortem network.
Makers and Quilters
Authors: MacArthur Cayley , Wong Caroline , Hancock Mark
Published: November 2019

Recent efforts to diversify participation in STEM (Science, Technology, Engineering & Math) activities through informal learning environments, such as hackathons and makerspaces, confirm a real desire for inclusion among potential female participants. However, understanding factors that may contribute to longer-term, sustainable diversification of such groups remains a challenge. In this paper, we present the results of a mixed-methods study of two microcosms of making: game development, and quilting. Our findings reveal parallel structures within these groups despite being highly skewed towards male or female participation, respectively. Our results shed light on attitudes, behaviours, and experiences indicating that similar desires for wider community support among other factors exist in both groups, but these needs are not satisfied in the STEM context. We conclude by discussing the implications of our findings as opportunities for rethinking how we design the environments that are meant to support design itself, considering the role of technology in these spaces, and prioritizing nurturing the development of the maker community beyond the maker space.
"The Most Trustworthy Coin"
Authors: Knittel Megan , Pitts Shelby , Wash Rick
Published: November 2019

Bitcoin is an innovative technological network, a new, non-governmental currency, and a worldwide group of users. In other words, Bitcoin is a complex sociotechnical system with a complex set of risks and challenges for anyone using it. We investigated how everyday users of Bitcoin develop trust in Bitcoin on one of the largest online communities devoted to Bitcoin: the Reddit.com r/bitcoin forum. Using qualitative content analysis, we examined how trust in Bitcoin develops based on contributions to this community. On r/bitcoin, trust in Bitcoin is driven by a pervasive ideology we call the "True Bitcoiner" ideology. This ideological viewpoint in centered on the interpretation of Bitcoin as functionally "trustless" and risk-free. Despite widespread evidence of emerging individual and system-level risks with using Bitcoin, participants continue to maintain this ideological perspective. This ideology consists of three primary beliefs: viewing Bitcoin's technology as more trustworthy than its people; rejecting 'corrupt' social hierarchies related to money; and the importance of accumulating or 'HODLing' quantities of Bitcoin as a strategy to create an ideal future. We conclude that this "True Bitcoiner" ideology is maintained despite contradictory evidence in the world because it allows participants to more easily interpret Bitcoin and make decisions by reducing perceived risk and uncertainty in the system. The role of this ideology on r/bitcoin demonstrates an expanded conceptualization of how trust is created and socially-mediated in socio-technical contexts.
Technological Frames and User Innovation
Authors: Kiene Charles , Jiang Jialun Aaron , Hill Benjamin Mako
Published: November 2019

Management of technological change in organizations is one of the most enduring topics in the literature on computer-supported cooperative work. The successful navigation of technological change is both more challenging and more critical in online communities that are entirely mediated by technology than it is in traditional organizations. This paper presents an analysis of 14 in-depth interviews with moderators of subcommunities of one technological platform (Reddit) that added communities on a new technological platform (Discord). Moderation teams experienced several problems related to moderating content at scale as well as a disconnect between the affordances of Discord and their assumptions based on their experiences on Reddit. We found that moderation teams used Discord's API to create scripts and bots that augmented Discord to make the platform work more like tools on Reddit. These tools were particularly important in communities struggling with scale. Our findings suggest that increasingly widespread end user programming allow users of social computing systems to innovate and deploy solutions to unanticipated design problems by transforming new technological platforms to align with their past expectations.
Dissonance Between Human and Machine Understanding
Authors: Zhang Zijian , Singh Jaspreet , Gadiraju Ujwal , Anand Avishek
Published: November 2019

Complex machine learning models are deployed in several critical domains including healthcare and autonomous vehicles nowadays, albeit as functional blackboxes. Consequently, there has been a recent surge in interpreting decisions of such complex models in order to explain their actions to humans. Models which correspond to human interpretation of a task are more desirable in certain contexts and can help attribute liability, build trust, expose biases and in turn build better models. It is therefore crucial to understand how and which models conform to human understanding of tasks. In this paper we present a large-scale crowdsourcing study that reveals and quantifies the dissonance between human and machine understanding, through the lens of an image classification task. In particular, we seek to answer the following questions: Which (well performing) complex ML models are closer to humans in their use of features to make accurate predictions? How does task difficulty affect the feature selection capability of machines in comparison to humans? Are humans consistently better at selecting features that make image recognition more accurate? Our findings have important implications on human-machine collaboration, considering that a long term goal in the field of artificial intelligence is to make machines capable of learning and reasoning like humans.
"I Think You'll Like It"
Authors: Xu Fengli , Han Zhenyu , Piao Jinghua , Li Yong
Published: November 2019

Understanding the roles of social factors in online purchase behavior has been a long standing research problem. The recently emerging social e-commerce platforms leverage the stimulated word-of-mouth effect to promote the sales of items, which offers a peek into the complex interplay between the social influence and online purchasing behavior. In this paper, we investigate this problem on a full-scale purchase behavior dataset from one of the leading social e-commerce platforms, Beidian. Specifically, we conduct a comparison study between the social e-commerce and conventional e-commerce that are both integrated in Beidian to examine how social factors affect user's purchase behavior. We reveal that social e-commerce leads to a 3.09~10.37 times higher purchase conversion rate compared with the conventional settings, which indicates users make purchase with significantly fewer item explorations. Then, we propose and validate four primary mechanisms that contribute to the efficient purchase conversion: better matching, social enrichment, social proof and price sensitivity. Moreover, we identify several behavioral indicators that are able to measure the effect of these mechanisms, based on which we design an accurate predictive model (AUC=0.7738) for user's purchase decision. These results combine to shed light on how to understand and model the purchase behavior in social e-commerce.
Collaboration Drives Individual Productivity
Authors: Murić Goran , Abeliuk Andres , Lerman Kristina , Ferrara Emilio
Published: November 2019

How does the number of collaborators affect individual productivity? Results of prior research have been conflicting, with some studies reporting an increase in individual productivity as the number of collaborators grows, while other studies showing that the free-rider effect skews the effort invested by individuals, making larger groups less productive. The difference between these schools of thought is substantial: if a super-scaling effect exists, as suggested by former studies, then as groups grow, their productivity will increase even faster than their size, super-linearly improving their efficiency. We address this question by studying two planetary-scale collaborative systems: GitHub and Wikipedia. By analyzing the activity of over 2 million users on these platforms, we discover that the interplay between group size and productivity exhibits complex, previously-unobserved dynamics: the productivity of smaller groups scales super-linearly with group size, but saturates at larger sizes. This effect is not an artifact of the heterogeneity of productivity: the relation between group size and productivity holds at the individual level. People tend to do more when collaborating with more people. We propose a generative model of individual productivity that captures the non-linearity in collaboration effort. The proposed model is able to explain and predict group work dynamics in GitHub and Wikipedia by capturing their maximally informative behavioral features, and it paves the way for a principled, data-driven science of collaboration.
Finding Language Classes
Authors: Weibert Anne , Krüger Max , Aal Konstantin , Salehee Setareh Sadat , Khatib Renad , Randall Dave , Wulf Volker
Published: November 2019

For migrants and refugees, settling in a host country often proves hugely problematic. The ability to communicate marks a significant step in the process of resettlement. The current high number of migrants coming to Europe has therefore meant that the need to improve and increase the availability of language provision has become more pressing. Nevertheless, due to the complexity of financial and legal regulations and of policy restrictions, access to and information about available courses are in practice hard to find, and non-funded volunteer initiatives are scarcely visible at all. To address this problem, a newly developed language-course wizard provides orientation for refugees and migrants. Findings indicate that its visual representation is apt to span a broad range of cultural as well as educational backgrounds. Our work demonstrates the need for a detailed approach to understanding the challenges that refugees and other migrants face in practice. Failing this, services frequently do not reach those they are intended for.
Exploring the Potential for Technology to Improve Cystic Fibrosis Care Provision
Authors: Rodger Sunil , O'Hara Kenton
Published: November 2019

Health care systems increasingly promote self-management of chronic conditions outside of traditional clinical environments, often through technologies which help to support patient self-care and engagement with medical professionals. We investigate specialist care provision in cystic fibrosis (CF), a life-shortening genetic condition, to understand the experiences of those living with it and of professionals who provide such care. Our work highlights how the motivations for the use of technology in this context are often intrinsically linked to the nature of CF itself and the constraints that the condition imposes on care provision. These include the high burden associated with self-management and clinic attendance; the ever-present risk of infection and a subsequent decline in health; and patients who are often very well-informed and actively engaged in their care. In exploring enablers and barriers to technology in this context, we highlight the importance of considering its integration into the chronic care cycles, practices, and structures of CF care.
Accessible Video Calling
Authors: Shi Lei , Tomlinson Brianna J. , Tang John , Cutrell Edward , McDuff Daniel , Venolia Gina , Johns Paul , Rowan Kael
Published: November 2019

Nonvisually Accessible Video Calling (NAVC) is a prototype that detects visual conversation cues in a video call and uses audio cues to convey them to a user who is blind or low-vision. NAVC uses audio cues inspired by movie soundtracks to convey Attention, Agreement, Disagreement, Happiness, Thinking, and Surprise. When designing NAVC, we partnered with people who are blind or low-vision through a user-centered design process that included need-finding interviews and design reviews. To evaluate NAVC, we conducted a user study with 16 participants. The study provided feedback on the NAVC prototype and showed that the participants could easily discern some cues, like Attention and Agreement, but had trouble distinguishing others. The accuracy of the prototype in detecting conversation cues emerged as a key concern, especially in avoiding false positives and in detecting negative emotions, which tend to be masked in social conversations. This research identified challenges and design opportunities in using AI models to enable accessible video calling.
The Social Infrastructure of Co-spaces
Authors: Lee Ahreum , Toombs Austin L. , Erickson Ingrid , Nemer David , Ho Yu-shen , Jo Eunkyung , Guo Zhuang
Published: November 2019

The rise of co-working and co-living spaces, as well as related shared spaces such as makerspaces and hackerspaces-a group we refer to as various types of "co-spaces" - has helped facilitate a parallel expansion of the "digital nomad (DN)" lifestyle. Digital nomads, colloquially, are those individuals that leverage digital infrastructures and sociotechnical systems to live location-independent lives. In this paper, we use Oldenburg's framework of a first (home), second (work), and third (social) place as an analytical lens to investigate how digital nomads understand the affordance of these different types of spaces. We present an analysis of posts and comments on the '/r/digitalnomad' subreddit, a vibrant online community where DNs ask questions and share advice about the different types of places and amenities that are necessary to pursue their digital nomad lifestyle. We found that places are often assessed positively or negatively relative to one primary characteristic: either they provide a means for nomads to maintain a clear separation between the social and professional aspects of their lives, or they provide a means to merge these aspects together. Digital nomads that favor the first type of place tend to focus on searching for factors that they feel will promote their own work productivity, whereas DNs that favor the second type of place tend to focus on factors that they feel will allow them to balance their work and social lives. We also build on linkages between the notion of a third place and the more recent theoretical construct of social infrastructure. Ultimately, we demonstrate how DNs' interests in co-spaces provide a kind of edge-case for CSCW and HCI scholars to explore how sociotechnical systems, such as variants of co-spaces, inform one another as well as signify important details regarding new ways of living and engaging with technology.
"Becoming Part of Something Bigger"
Authors: King Jennifer
Published: November 2019

Direct to consumer genetic testing (DTCGT) services where users can identify their inherited diseases and traits, find genetic relatives, and learn more about their ethnic heritage continue to grow in popularity. At the same time, one's DNA is one of the most identifiable, immutable forms of personal information, and sharing it carries risks to one's privacy. What motivates individuals to engage in DTCGT, and what are the implications for information privacy at both the individual and societal levels? This study uses qualitative interviews with ten customers of the DTCGT service 23andMe to explore why they engaged in DTCGT, the benefits they received, their expectations of privacy, and perceptions of risk. It also introduces the use of social exchange theory as a theoretical framework for examining the social dimensions of information privacy and personal disclosure. The findings demonstrate that the participants' assumptions of anonymity, as well as their their belief that their contributions to online genetic databases aid the public good, were key motivating factors. The participants were generally unaware of the potential risks to their individual genetic privacy as well as the impact of large scale genetic testing databases on networked, collective privacy. The findings demonstrate that framework of social exchange theory aids in understanding how the form of the relationship affected the participants' decisions to disclose their personal information to 23andMe as well as their perceptions of risk in the DTCGT context.
Home Worlds: Situating Domestic Computing in Everyday Life Through a Study of DIY Home Repair
Authors: Wolf Christine , Ringland Kathryn E. , Hayes Gillian
Published: November 2019

We draw on a qualitative study of homeowners who engage in do-it-yourself (DIY) home repair and introduce "home worlds" as a conceptual lens to understand how interactions with the home as a built environment (local and mechanical engagements with its material components) are situated in broad, diffuse, and constraint-rich social worlds. A "home worlds" perspective challenges domestic computing inquiries to adopt a broader orientation when considering a home's users and requirements; our case of home repair, in particular, provokes us to consider the home as embedded in communities and framed in relation to the precarious constraints of everyday life. We discuss how these insights open up new avenues for future research and design of collaborative domestic computing technologies. ?
How Presenters Perceive and React to Audience Flow Prediction In-situ
Authors: Sun Wei , Li Yunzhi , Tian Feng , Fan Xiangmin , Wang Hongan
Published: November 2019

The degree and quality of instructor-student interactions are crucial for students' engagement, retention, and learning outcomes. However, such interactions are limited in live online lectures, where instructors no longer have access to important cues such as raised hands or facial expressions at the time of teaching. As a result, instructors cannot fully understand students' learning progresses. This paper presents an explorative study investigating how presenters perceive and react to audience flow prediction when giving live-stream lectures, which has not been examined yet. The study was conducted with an experimental system that can predict audience's psychological states (e.g., anxiety, flow, boredom) through real-time facial expression analysis, and can provide aggregated views illustrating the flow experience of the whole group. Through evaluation with 8 online lectures (N_instructors=8, N_learners=21), we found such real-time flow prediction and visualization can provide value to presenters. This paper contributes a set of useful findings regarding their perception and reaction of such flow prediction, as well as lessons learned in the study, which can be inspirational for building future AI-powered system to assist people in delivering live online presentations.
Content Removal as a Moderation Strategy
Authors: Srinivasan Kumar Bhargav , Danescu-Niculescu-Mizil Cristian , Lee Lillian , Tan Chenhao
Published: November 2019

Moderators of online communities often employ comment deletion as a tool. We ask here whether, beyond the positive effects of shielding a community from undesirable content, does comment removal actually cause the behavior of the comment's author to improve? We examine this question in a particularly well-moderated community, the ChangeMyView subreddit.

The standard analytic approach of interrupted time-series analysis unfortunately cannot answer this question of causality because it fails to distinguish the effect of having made a non-compliant comment from the effect of being subjected to moderator removal of that comment. We therefore leverage a "delayed feedback" approach based on the observation that some users may remain active between the time when they posted the non-compliant comment and the time when that comment is deleted. Applying this approach to such users, we reveal the causal role of comment deletion in reducing immediate noncompliance rates, although we do not find evidence of it having a causal role in inducing other behavior improvements. Our work thus empirically demonstrates both the promise and some potential limits of content removal as a positive moderation strategy, and points to future directions for identifying causal effects from observational data.
Birds of a Feather Clock Together
Authors: Das Swain Vedant , Reddy Manikanta D. , Nies Kari Anne , Tay Louis , De Choudhury Munmun , Abowd Gregory D.
Published: November 2019

Organizations often strive to recruit and retain individuals who would be a "good fit" with their core values, beliefs and practices. Person-Organization (P-O congruence is known to explain employee satisfaction, commitment and absenteeism. This paper proposes a new measure of P-O fit by empirically investigating the similarity of routine within an organization. This measure of routine fit is motivated by the theory of entrainment, which refers to the synchrony of individual and community behaviors. We use unobtrusive bluetooth sensing to examine how the concurrence of latent activity patterns is related to job performance and wellbeing. Routine fit echoes traditional constructs of congruence as it is significantly related to higher task performance and lower workplace deviance. Additionally however, it is also related to greater stress and higher arousal. Prior work in organizational psychology have used single-occasion survey instruments to infer uni-dimensional models of fit. These methods are limited by subjective perceptions of employees. In contrast, we demonstrate a data-driven and multidimensional approach to study normative routines in an organization as a measure of P-O fit. We discuss the potential of our approach in designing technologies that understand the congruence of employee routines and positively impact employee functioning at the workplace.
"Parar-daktar Understands My Problems Better"
Authors: Sultana Sharifa , Ahmed Syed Ishtiaque , Fussell Susan R.
Published: November 2019

This paper discusses the issues that arise while designing better wellbeing support for a low-income rural population in Bangladesh. Through a four-month long ethnographic study, we explored how people in 13villages in southwestern Bangladesh accessed healthcare. Over the course of our fieldwork, we asked the participants about the existing healthcare services available to them and how they interacted with different ICT-based wellbeing support systems. Our findings show that insufficient resources, schedules, and the distant location of government-supported healthcare facilities were major challenges for the villagers. We also found that villagers' limited knowledge and mistrust of care-providing infrastructure block them from the benefits of available ICT-based supports and resources. Drawing on our findings from the field, we discuss possible alternative design directions for improving wellbeing support for rural Bangladeshis.
Crossmod: A Cross-Community Learning-based System to Assist Reddit Moderators
Authors: Chandrasekharan Eshwar , Gandhi Chaitrali , Mustelier Matthew Wortley , Gilbert Eric
Published: November 2019

In this paper, we introduce a novel sociotechnical moderation system for Reddit called Crossmod. Through formative interviews with 11 active moderators from 10 different subreddits, we learned about the limitations of currently available automated tools, and how a new system could extend their capabilities. Developed out of these interviews, Crossmod makes its decisions based on cross-community learning---an approach that leverages a large corpus of previous moderator decisions via an ensemble of classifiers. Finally, we deployed Crossmod in a controlled environment, simulating real-time conversations from two large subreddits with over 10M subscribers each. To evaluate Crossmod's moderation recommendations, 4 moderators reviewed comments scored by Crossmod that had been drawn randomly from existing threads. Crossmod achieved an overall accuracy of 86% when detecting comments that would be removed by moderators, with high recall (over 87.5%). Additionally, moderators reported that they would have removed 95.3% of the comments flagged by Crossmod; however, 98.3% of these comments were still online at the time of this writing (i.e., not removed by the current moderation system). To the best of our knowledge, Crossmod is the first open source, AI-backed sociotechnical moderation system to be designed using participatory methods.
Head-mounted Displays, Smartphones, or Smartwatches? -- Augmenting Conversations with Digital Representation of Self
Authors: Hirskyj-Douglas Ilyena , Kytö Mikko , McGookin David
Published: November 2019

Technologies that augment face-to-face interactions with a digital sense of self have been used to support conversations. That work has employed one homogenous technology, either 'off-the-shelf' or with a bespoke prototype, across all participants. Beyond speculative instances, it is unclear what technology individuals themselves would choose, if any, to augment their social interactions; what influence it may exert; or how use of heterogeneous devices may affect the value of this augmentation. This is important, as the devices that we use directly affect our behaviour, influencing affordances and how we engage in social interactions. Through a study of 28 participants, we compared head-mounted display, smartphones, and smartwatches to support digital augmentation of self during face-to-face interactions within a group. We identified a preference among participants for head-mounted displays to support privacy, while smartwatches and smartphones better supported conversational events (such as grounding and repair), along with group use through screen-sharing. Accordingly, we present software and hardware design recommendations and user interface guidelines for integrating a digital form of self into face-to-face conversations.
Gallery D.C.: Design Search and Knowledge Discovery through Auto-created GUI Component Gallery
Authors: Chen Chunyang , Feng Sidong , Xing Zhenchang , Liu Linda , Zhao Shengdong , Wang Jinshui
Published: November 2019

Online communities like Dribbble and GraphicBurger allow GUI designers to share their design artwork and learn from each other. These design sharing platforms are important sources for design inspiration, but our survey with GUI designers suggests additional information needs unmet by existing design sharing platforms. First, designers need to see the practical use of certain GUI designs in real applications, rather than just artworks. Second, designers want to see not only the overall designs but also the detailed design of the GUI components. Third, designers need advanced GUI design search abilities (e.g., multi-facets search) and knowledge discovery support (e.g., demographic investigation, cross-company design comparison). This paper presents Gallery D.C. http://mui-collection.herokuapp.com/, a gallery of GUI design components that harness GUI designs crawled from millions of real-world applications using reverse-engineering and computer vision techniques. Through a process of invisible crowdsourcing, Gallery D.C. supports novel ways for designers to collect, analyze, search, summarize and compare GUI designs on a massive scale. We quantitatively evaluate the quality of Gallery D.C. and demonstrate that Gallery D.C. offers additional support for design sharing and knowledge discovery beyond existing platforms.
WeBuildAI
Authors: Lee Min Kyung , Kusbit Daniel , Kahng Anson , Kim Ji Tae , Yuan Xinran , Chan Allissa , See Daniel , Noothigattu Ritesh , Lee Siheon , Psomas Alexandros , Procaccia Ariel D.
Published: November 2019

Algorithms increasingly govern societal functions, impacting multiple stakeholders and social groups. How can we design these algorithms to balance varying interests in a moral, legitimate way? As one answer to this question, we present WeBuildAI, a collective participatory framework that enables people to build algorithmic policy for their communities. The key idea of the framework is to enable stakeholders to construct a computational model that represents their views and to have those models vote on their behalf to create algorithmic policy. As a case study, we applied this framework to a matching algorithm that operates an on-demand food donation transportation service in order to adjudicate equity and efficiency trade-offs. The service's stakeholders--donors, volunteers, recipient organizations, and nonprofit employees--used the framework to design the algorithm through a series of studies in which we researched their experiences. Our findings suggest that the framework successfully enabled participants to build models that they felt confident represented their own beliefs. Participatory algorithm design also improved both procedural fairness and the distributive outcomes of the algorithm, raised participants' algorithmic awareness, and helped identify inconsistencies in human decision-making in the governing organization. Our work demonstrates the feasibility, potential and challenges of community involvement in algorithm design.
"Did You Suspect the Post Would be Removed?"
Authors: Jhaver Shagun , Appling Darren Scott , Gilbert Eric , Bruckman Amy
Published: November 2019

Thousands of users post on Reddit every day, but a fifth of all posts are removed. How do users react to these removals? We conducted a survey of 907 Reddit users, asking them to reflect on their post removal a few hours after it happened. Examining the qualitative and quantitative responses from this survey, we present users' perceptions of the platform's moderation processes. We find that although roughly a fifth (18%) of the participants accepted that their post removal was appropriate, a majority of the participants did not --- over a third (37%) of the participants did not understand why their post was removed, and further, 29% of the participants expressed some level of frustration about the removal. We focus on factors that shape users' attitudes aboutfairness in moderation andposting again in the community. Our results indicate that users who read community guidelines or receive explanations for removal are more likely to perceive the removal as fair and post again in the future. We discuss implications for moderation practices and policies. Our findings suggest that the extra effort required to establish community guidelines and educate users with helpful feedback is worthwhile, leading to better user attitudes about fairness and propensity to post again.
The Tools of Management
Authors: Khovanskaya Vera , Dombrowski Lynn , Rzeszotarski Jeffrey , Sengers Phoebe
Published: November 2019

At the same time that workers' rights are generally declining in the United States (US), workplace computing systems gather more data about workers and their activities than ever before. The rise of large scale labor analytics raises questions about how and whether workers could use such data to advocate for their own goals. Here, we analyze the historical development of workplace technology design methods in CSCW to show how mid-20th century labor responses to scientific management can inform directions in contemporary digital labor advocacy. First, we demonstrate how specific methodological tendencies from industrial scientific management were adapted to work in CSCW, and then subsequently altered in crowd work and social computing research to more closely resemble industrial approaches. Next, we show how three tactics used by labor unions to strategically engage with industrial scientific management in the mid-20th century can inform data-driven worker advocacy in platform-mediated work. Finally, we discuss how this history shapes our understanding of worker participation and the implications of using worker data for contemporary advocacy goals.
Deconstructing Community-Based Collaborative Design
Authors: Harrington Christina , Erete Sheena , Piper Anne Marie
Published: November 2019

Participatory Design (PD) is envisioned as an approach to democratizing innovation in the design process by shifting the power dynamics between researcher and participant. Recent scholarship in HCI and design has analyzed the ways collaborative design engagements, such as PD situated in the design workshop can amplify voices and empower underserved populations. Yet, we argue that PD as instantiated in the design workshop is very much an affluent and privileged activity that often neglects the challenges associated with envisioning equitable design solutions among underserved populations. Based on two series of community-based PD workshops with underserved populations in the U.S., we highlight key areas of tension and considerations for a more equitable PD approach: historical context of the research environment, community access, perceptions of materials and activities, and unintentional harm in collecting full accounts of personal narratives. By reflecting on these tensions as a call-to-action, we hope to deconstruct the privilege of the PD workshop within HCI and re-center the focus of design on individuals who are historically underserved.
Learning to Airbnb by Engaging in Online Communities of Practice
Authors: Holikatti Maya , Jhaver Shagun , Kumar Neha
Published: November 2019

Technological advances, combined with sustained, minimalist consumerism, have raised the popularity of sharing economy platforms like Airbnb and Uber. These platforms are considered to have disrupted traditional industries and revolutionized how consumers interact with their services. The Computer-Supported Cooperative Work (CSCW) community has researched various aspects of the sharing economy; however, it is unclear how novices grow into experts in its various instantiations. In this paper, we present a qualitative investigation of Airbnb hosts, and Facebook groups in which they participate, for an enriched understanding of their learning mechanisms. Drawing on the theory of Legitimate Peripheral Participation (LPP), our findings highlight the learning mechanisms that enable novice hosts to transition from partaking in peripheral roles to becoming integrated members of their (Facebook) communities of practice. We also present recommendations for sharing economy platforms, micro-entrepreneurs, and the online communities that serve them both.
Recalling the early days (first decade) of SIGCOMM and thoughts on future research directions
Authors: Chu Wesley W.
Published: November 2019

ACM SIGCOMM has reached its fiftieth birthday. The field is still remarkably strong, expanding into new disciplines as well as new application areas. Since I was an early SIGCOMM chair (1973-1977), I have been asked to recall the early days and discuss possible future directions.
About velocity and dealing with "fake" scientific news
Authors: Diot Christophe
Published: November 2019

When I embarked on the CCR adventure 15 years ago I did not expect it to be so exciting, fruitful, and life changing. I am describing here our motivation and approach, our successes and failures, with I hope a perceptible sense of humor.
Looking back at being the editor of CCR (2013--2016)
Authors: Papagiannaki Konstantina (Dina)
Published: November 2019

Our community is celebrating 50 years and I was asked to provide my perspective on one of its longest standing communication vehicles, ACM SIGCOMM Computer Communication Review, as one of its editors.
Retrospective on "fragmentation considered harmful"
Authors: Mogul Jeffrey C. , Kantarjiev Christopher A
Published: November 2019

We look back at our 1987 paper, "Fragmentation Considered Harmful," to explain why we wrote it, how the prevalence of fragmentation was reduced by approaches such as Path MTU Discovery, and how fragmentation-related issues still lurk in today's Internet. Our paper listed several reasons why we thought fragmentation was harmful; some were more true in 1987 than they are today, and after our paper was published, the community realized that fragmentation (and the mechanisms used to mitigate it) exposed harms we did not anticipate in our paper.
Retrospective on "measured capacity of an ethernet: myths and reality"
Authors: Mogul Jeffrey C. , Kantarjiev Christopher A
Published: November 2019

The original Ethernet design used CSMA/CD on a broadcast cable. Even after it became commercially popular, many people expressed concerns that Ethernet could not efficiently use the full channel bandwidth. In our 1988 paper, "Measured Capacity of an Ethernet: Myths and Reality," we reported on experiments we ran showing that, even under relatively heavy loads, Ethernet typically still performed well. We describe the context in which we ran those experiments, and some subsequent research conducted by others.
Perspective
Authors: Vasisht Deepak , Kumar Swarun , Rahul Hariharan , Katabi Dina
Published: November 2019

The ever-increasing demand for data has forced cellular networks towards advanced multi-antenna (MIMO) techniques. However, advanced MIMO solutions such as massive MIMO, coordinated multi-point, distributed MIMO, and multi-user MIMO, all require the base station to know the downlink channels to the client. In the absence of this information, the base station cannot beamform its signal to its users. Therefore, base stations require user devices to perform the measurements and send the channels back to the basestation as feedback. This feedback generates significant overhead that scales linearly with the number of antennas, and is a bottleneck for next generation of cellular networks with large antenna deployments.
Certifying approximate solutions to polynomial systems on Macaulay2
Authors: Lee Kisun
Published: November 2019

We present the Macaulay2 package NumericalCertification for certifying roots of square polynomial systems. It employs the interval Krawczyk method and
α
-theory as main methods for certification. The package works with output data computed in Macaulay2 with no need for external software. Also, our implementation supports the Krawczyk method which uses interval arithmetic.
The conference "computer algebra" in Moscow
Authors: Abramov Sergei A. , Ryabenko Anna , Sevastianov Leonid A. , Wu Min , Zonn Yvette
Published: November 2019

The International Conference "Computer Algebra"was held in Moscow, Russia from June 17-21, 2019. The conference web-site is http://www.ccas.ru/ca/conference. Co-organized by the Dorodnicyn Computing Centre (Federal Research Center "Computer Science and Control") of Russian Academy of Sciences and the Peoples' Friendship University of Russia, it was devoted to computer algebra and related topics.

This is the third edition of the conference, and the previous two were in 2016 and 2017, respectively.
An adaptive rendering framework for efficient synthetic light field generation
Authors: Tseng Liang-Chi , Hsu Wei-Chung
Published: November 2019

Real-time global illumination rendering is very desirable for emerging applications such as Virtual Reality (VR) and Augmented Reality (AR). However, client devices have difficulties to support photo-realistic rendering, such as Ray-Tracing, due to insufficient computing resources. Many modern frameworks adopted Light Field rendering to support device displaying. A Light Field can be precomputed and stored in the Cloud. During runtime, the display extracts the color information from the Light Field to generate arbitrary real time viewpoints or re-focusing within a predefined area. To efficiently compute the Light Field, We have combined DIBR (Depth-Image-Based-Rendering) and traditional ray-tracing in an adaptive fashion to synthesize images. By measuring the color errors during runtime, we adaptively determine a good balance between DIBR and Ray Tracing. We study several cases and problems when combing these algorithms and came up with a more efficient solution. To further optimize the computation efficiency, we also added a multi-level design to exploit the degree of shareable pixels among images to control the computation for error reduction. In addition, we also design an efficient multi-threading scheduling to show the scalability of our approach. Experiments show that when the number of threads is small, we achieved up to 3.24X speedup in Light Field generation for relative simple scenes like Cornell Box, and about 2X speed up for complex scenes like Conference Room or Sponza. In the multi-thread environment, our proposed scheme can offer about 2X speedup over traditional ones.
A novel methodology for rat aortic pulse wave velocity assessment by Doppler ultrasound: validation against invasive measurements
Authors: Wang Zhen , Fu Zihao , Yang Yong , Xing Wenjuan , Zhang Xing , Wang Jiaping , Li Yongzhi , Yuan Lijun , Gao Feng
Published: November 2019

There is still lack of a simple, accurate, and noninvasive method for rat aortic pulse wave velocity (PWV) measurement, especially the transit distance cannot be accurately measured. Thus, we aimed to derive an equation for aortic transit distance as a function of the nose-to-rump length ( L) and to test the hypothesis that aortic PWV measured by new equation combined with Doppler ultrasound (the “equation method”) may have stronger correlation with invasive measurements than traditional “body surface method.” Two-hundred male Sprague-Dawley (SD) rats (age ranged 5–24 wk) were included in protocol 1, and the aortic transit distances were measured postmortem. In protocol 2, heart-femoral PWV and carotid-femoral PWV were measured by equation method (hfPWVE, cfPWVE) and also by traditional body surface method (hfPWVS, cfPWVS) in another 30 young and 28 old rats. These measurements were then validated against invasively measured hfPWVI and cfPWVI from the same animal. Protocol 1 showed that the heart-femoral transit distance could be calculated by 0.6086 × L − 1.6523, and the carotid-femoral transit distance by 0.4614 × L + 1.8335. In protocol 2, in young rats, the Pearson r between hfPWVE, cfPWVE, hfPWVS, and cfPWVS and their corresponding invasive measurement were 0.8962, 0.8509, 0.8387, and 0.7828, respectively (all P < 0.0001). In the old group, the results were 0.8718, 0.7999, 0.8330, and 0.7112, respectively (all P < 0.0001). The hfPWVE and cfPWVE showed better agreement with hfPWVI and cfPWVI and lower intra- and interobserver variability compared with hfPWVS and cfPWVS in both groups. These findings demonstrate that this novel methodology provides a simple and reliable method for rat noninvasive aortic PWV measurement.

NEW & NOTEWORTHY First, when measuring aortic PWV in SD rat models, the heart-femoral transit distance can be estimated by 0.6086 × L − 1.6523, and the carotid-femoral distance transit distance can be estimated by 0.4614 × L + 1.8335, where L (in mm) is nose-to-rump length. Second, this novel methodology for aortic PWV measurement was validated with a closer correlation with the invasive measurements than traditional approach in young and old rats. Third, this study provides a simple and reliable method for rat noninvasive aortic PWV measurement.