Social Futures Lab
Various Presenters (Allen School)
Colloquium
Thursday, November 3, 2022, 3:30 pm
Abstract
Speaker: Ruotong Wang
Title: Connected Conversations: Designing Information Artifacts that Bridge between Remote Synchronous and Asynchronous Communication
Collaboration is increasingly happening remotely, with communication between collaborators conducted both synchronously, in group calls, as well as asynchronously, in settings such as group chat, email, and shared documents. In this environment, the struggle to keep track of information is exacerbated, as information from synchronous conversations can be hard to access after the fact and have little connection to information generated in asynchronous settings. In this work, we seek to understand the ways people navigate information exchange between remote synchronous meetings and asynchronous understanding and follow-on discussion and collaboration. Via formative interviews with 13 participants and a survey with 198 participants, we find that common artifacts from meetings such as notes have drawbacks for asynchronous usage, with people not always trusting others' notes or willing to share their notes. People have even fewer uses for meeting recordings---even when recordings are taken, people rarely go back to them or share them with others.
These results lead us to investigate the opportunities for designing novel post-synchronous bridging artifacts that can more effectively bridge from remote synchronous meetings toward various desired asynchronous interactions. We conducted co-design sessions with 16 participants to understand the characteristics people want for these artifacts, finding that participants desired designs that enable them to consume the meeting contents asynchronously, share contextualized meeting summaries out to others, and evolve the artifact over time. We conclude with an identification of three key tensions in user desires and possible ways these tensions can be negotiated in the design of post-meeting information artifacts.
Bio:
Ruotong Wang is a third-year Ph.D. student at the University of Washington, advised by Prof. Amy Zhang. Her research interests are at the intersection of Social Computing and Human-AI interaction. In her research, she is interested in designing AI-powered interactive tools to support communication and collaboration in teams.
===
Speaker: Kevin Feng
Title: Examining the Impact of Provenance-Enabled Media on Trust and Agreement in Social Media Feeds
In recent years, industry leaders and academic researchers have proposed the use of technical provenance standards to combat visual misinformation propagated by digitally altered media. By allowing provenance information such as authorship and edit date to be immutably and securely chained onto media metadata, users on content platforms such as social media can make a more informed decision about the validity of media they encounter. However, it is unclear how end users will respond to the presence of this information in online settings where it is common to encounter media of varying provenance, despite its importance to the successful adoption of usable provenance systems. It is also unclear how to best design media provenance indicators so that users understand what is being conveyed. In this work, we conducted an online experiment with 595 participants from the US and UK to investigate how user perceptions of media credibility---as defined by trust judgment and truth evaluation---changed upon the introduction of provenance information in a social media feed.
We found overall that provenance mostly lowered trust and caused users to doubt the truth of deceptive media, particularly when the credibility of the provenance information itself was uncertain. Although provenance was helpful in correcting initially misled truth judgements in deceptive media, it led participants farther away from the truth in some honest media. Our findings show that provenance, although enlightening in some cases, is still not a concept well-understood by users, and that provenance credibility can be easily confused with the orthogonal (albeit related) concept of media credibility. We conclude with implications on the design of usable provenance systems going forward, with an emphasis on conceptual clarity in provenance-enabled interfaces and user education.
Bio: Kevin Feng is a 2nd year PhD student working with David McDonald (HCDE) and Amy Zhang (CSE) in the areas of social computing and HCI. He is broadly interested in tools and techniques that empower non-experts to leverage emerging technologies for their own domain-specific needs, often aided by collaboration and collective sensemaking.
===
Speaker: Jim Chen
Title: Understanding and Addressing Uncertainty of the Crowd
Uncertainty is an important factor that is crucial when it comes to understanding human
judgments. Whether it’s annotators producing data used to train and evaluate machine learning systems, teaching staff assigning grades to open-ended student responses, or online communities adjudicating the moderation action to apply to a piece of content, many groups and individuals need to account for and address the uncertainty that comes along with conducting judgments. As the application of computing technology expands to more areas of society, groups and individuals are faced with the need to make judgments on increasingly complex, subjective, and nuanced tasks.
In this talk, I will present an overview of my work consisting of a set of novel annotation tools and workflow designs that support capturing, distinguishing, and addressing uncertainty throughout each step involved in making group judgments. Specifically, I will talk about: (1) how we can use ranges to better capture and distinguish sources of uncertainty in scalar rating tasks; (2) how we can use precedents to interact with uncertainty in categorical decision tasks; (3) how we can address disagreements to reduce uncertainty through pairwise multi-turn deliberation; and (4) how we can dynamically select targeted interventions for reducing uncertainty.
Bio: Jim Chen is a final year PhD student (graduating this quarter) in CSE advised by Amy Zhang. He’s broadly interested in the intersection of HCI, crowdsourcing, and social computing. For his dissertation work, he primarily tackled the problem of creating better tools to support understanding and addressing uncertainty in human judgments.
===
Title: FilterBuddy: Designing Word Filter Tools for Creator-led Comment Moderation
Online social platforms centered around content creators often allow comments on content, where creators moderate the comments they receive. As creators can face overwhelming numbers of comments, with some of them harassing or hateful, platforms typically provide tools such as word filters for creators to automate aspects of moderation. From needfinding interviews with 19 creators about how they use existing tools, we found that they struggled with writing good filters as well as organizing and revisiting their filters, due to the difficulty of determining what the filters actually catch.
To address these issues, we present FilterBuddy, a system that supports creators in authoring new filters or building from existing filter lists, as well as organizing their filters and visualizing what comments are captured over time. We conducted an early-stage evaluation of FilterBuddy with YouTube creators, finding that participants see FilterBuddy not just as a moderation tool, but also a means to organize their comments to better understand their audiences.
Bio: Shagun Jhaver is currently an Assistant Professor in the Department of Library and Information Science in the School of Communication and Information at Rutgers University. His research is focused on understanding and addressing online harms. In his work, he studies how the design, technical affordances, and policies around governance mechanisms of internet platforms affect public discourse, and explores how platforms can address societal issues such as online harassment and the rise of hate groups.
(Note: This project will be presented by Jim Chen)
===
Speaker: Galen Weld
Title: What Makes Online Communities 'Better'? Measuring Values, Consensus, and Conflict across Thousands of Subreddits
Making online social communities ‘better’ is a challenging undertaking, as online communities are extraordinarily varied in their size, topical focus, and governance. As such, what is valued by one community may not be valued by another. However, community values are challenging to measure as they are rarely explicitly stated. In this work, we measure community values through the first large-scale survey of community values, including 2,769 reddit users in 2,151 unique subreddits. Through a combination of survey responses and a quantitative analysis of publicly available reddit data, we characterize how these values vary within and across communities. Amongst other findings, we show that community members disagree about how safe their communities are, that longstanding communities place 30.1% more importance on trustworthiness than newer communities, and that community moderators want their communities to be 56.7% less democratic than non-moderator community members. These findings have important implications, including suggesting that care must be taken to protect vulnerable community members, and that participatory governance strategies may be difficult to implement. Accurate and scalable modeling of community values enables research and governance which is tuned to each community's different values. To this end, we demonstrate that a small number of automatically quantifiable features capture a significant yet limited amount of the variation in values between communities with a ROC AUC of 0.667 on a binary classification task. However, substantial variation remains, and modeling community values remains an important topic for future work. We make our models and data public to inform community design and governance.
Bio:Galen Weld is a 5th year PhD student in the Paul G. Allen School of Computer Science and Engineering, where he is advised by Tim Althoff and Amy Zhang. His research focuses on the governance and moderation of online communities, especially on reddit. Galen is a long-time moderator of several reddit communities and is on the reddit Moderator Council.