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Unmanned Ground Vehicles: Transforming the Future of Autonomous Land Operations
by wadekar.sagar087＠gmail.com 01 Nov '26

01 Nov '26

Unmanned Ground Vehicles (UGVs) are becoming an important part of modern robotics, automation, and defense operations. These ground-based robotic systems are designed to perform tasks without requiring a human operator to be physically present inside the vehicle. Depending on their design and capabilities, they can operate through remote control, autonomous navigation, or a combination of both technologies. The development of Unmanned Ground Vehicles is closely associated with advancements in artificial intelligence, machine learning, computer vision, and sensor technologies. These systems use cameras, LiDAR, GPS, radar, and other navigation tools to identify obstacles, understand surrounding environments, and perform assigned operations. Their applications extend across several industries, including military operations, agriculture, logistics, mining, construction, and emergency response. In the defense sector, UGVs are increasingly being explored for surveillance, reconnaissance, explosive ordnance disposal, transportation of supplies, and operations in hazardous environments. Their ability to access difficult or dangerous locations can help reduce direct human exposure to operational risks. In commercial applications, autonomous ground robots are being deployed for warehouse transportation, industrial inspection, material handling, and agricultural monitoring. Despite their growing capabilities, several challenges influence the broader adoption of these systems. High development costs, battery limitations, communication disruptions, cybersecurity risks, and difficulties navigating unpredictable terrain remain important technical considerations. Ensuring reliable decision-making and safe human-machine interaction is also essential for autonomous ground operations. As robotics technologies continue to evolve, unmanned ground systems are expected to become more adaptable, intelligent, and efficient. Their integration with autonomous platforms, advanced sensors, and connected digital infrastructure could reshape how organizations approach transportation, industrial automation, security, and operations in challenging environments. https://www.marketresearchfuture.com/reports/unmanned-ground-vehicles-marke…

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Dionna Taylor at APHA 2026: Disease Burden and Online Health Discussion
by Community Data Science Collective 30 Oct '26

30 Oct '26

Post : Dionna Taylor at APHA 2026: Disease Burden and Online Health Discussion URL : https://blog.communitydata.science/dionna-taylor-at-apha-2026-disease-burde… Posted : October 30, 2026 at 16:18 Author : Community Data Science Collective Categories : Conferences and Presentations Dionna Taylor will be in San Antonio this coming week to present at the APHA 2026 Annual Meeting and Expo ( https://www.apha.org/events-and-meetings/annual ) between November 1–4. We believe this is the first time anybody from the collective has been to APHA, so please stop by and say hi or reach out to Dionna! https://blog.communitydata.science/wp-content/uploads/sites/5/2026/10/apha2… Sunday, November 1, 1:00–2:00 pm (Henry B. González Convention Center, Row 12 – Board 6, Student Poster Competitions I) Dionna will present "Determinants of online health discussions: A disease burden perspective ( https://apha.confex.com/apha/2026/meetingapp.cgi/Paper/593193 ) " as part of the Applied Public Health Statistics student poster competition. The project asks why some health conditions get far more attention online than others. Dionna matched 183 health conditions from the Global Burden of Disease dataset to Reddit posts and measured each condition's stigma using word embeddings. The study found that the volume of discussion tracks disease burden, measured in disability-adjusted life years (DALYs), more closely than it tracks stigma or prevalence. The results suggest that combining population health metrics with computational methods can show where online attention matches public health need and where it falls short. Add a comment to this post: https://blog.communitydata.science/dionna-taylor-at-apha-2026-disease-burde… -- Manage Subscriptions https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email… Unsubscribe: https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email…

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Report back from CSCW 2026
by Community Data Science Collective 18 Oct '26

18 Oct '26

Post : Report back from CSCW 2026 URL : https://blog.communitydata.science/report-back-from-cscw-2026/ Posted : October 18, 2026 at 20:23 Author : Nate TeBlunthuis Tags : artificial intelligence, conference, cscw, free/libre open source software Categories : Conferences and Presentations, Reflections, Uncategorized @groceryheist, @yiweiwu, @kaylea, and @mako attended CSCW 2026 from Oct 10 through Oct 14. A previous blog post ( https://blog.communitydata.science/cdsc-at-cscw-2026-rules-knowledge-gaps-a… ) covers our presentations. Here we're sharing some takeaways and highlights from the conference. I (Nate) wrote this post, so it naturally reflects my views most, but I'm also drawing on my conversations with the other CDSC attendees. Takeaways from OSS + AI Workshop Kaylea Champion, Benjamin Mako Hill, and Matt Gaughan helped organize a CSCW workshop ( https://wiki.communitydata.science/OSS_AI_Workshop_(CSCW_2026) ) on Open Source Software and artificial intelligence, and Kaylea, Mako, and Nate attended. The workshop was conceived and framed as a conversation focused on problems open source practitioners have raised related to building sustainable collaborative software projects in the open. However, I was both astonished and energized by how workshop participants' focus seemed to shift toward more foundational and future-looking questions about the nature of collaboration and its role in software production in the first place. Kaylea shared how the OSS developers she has interviewed recently are using AI intensively and enthusiastically, and Mako seemed joyous at the fun he's been having contributing in previously unimagined ways to projects like LaTeX. But even though AI seems to make open source developers more productive, it also raises the question: what makes code worth sharing at all? Nate shared how he's used Claude Code to create a bespoke application for data annotation, and then three other attendees described doing the same thing. Should we share these software projects, even if they are idiosyncratic? How do ubiquitous AI tools change the role of open software and knowledge commons when the value of a project shifts from its code or features (which may be easy to replicate) to its reputation, trustworthiness, ubiquity, or role in a project ecosystem? Mako, building on insights he also shared in a presentation at UT Austin in September about his new book Peer Production ( https://mitpress.mit.edu/9780262054805/peer-production/ ) in the MIT Press Essential Knowledge Series (co-authored with Aaron Shaw and Christian Pentzold; available open access here ( https://direct.mit.edu/books/book/6212/Peer-Production ) ), described a potentially deeper threat AI poses to Open Source now that Open Source developers are using AI coding tools. If I use a "frontier" agent to write a patch, and it generates buggy or otherwise inadequate code that I fix, it sends my corrections back to its company, which can use this information to train the next model version. In this way, AI agents collect knowledge from open source developers and aggregate it into new models, which their companies can then sell back to open source developers. This distributed production of knowledge, which is then aggregated and disseminated, resembles a peer production process, only the aggregate artifact is a private good (although distillation of open-weight models may transmit some of this knowledge into a commons in some sense). A CSCW poster ( https://dl.acm.org/doi/full/10.1145/3785651.3831559 ) by Caitlin Morris and Pattie Maes presented a system that I found really interesting for envisioning future modes of knowledge sharing among collaborators using AI tools. Notes from the Lasting Impact Award The question "what's CSCW's role in AI research?" was asked in one form or another in panels and conversations at CSCW 2026. Does CSCW need to jump on the AI bandwagon and study industry-facing problems? Maybe, but what makes that different from mainstream AI or NLP research? Should CSCW focus critically on social problems related to AI? Certainly, but that work also happens at FAccT among other conferences. What does CSCW have to contribute that other fields wouldn't? Surprisingly, I found one of the most compelling answers in Nikki Kittur's presentation at the session on the lasting impact award he received with Robert Kraut for their 2008 paper "Harnessing the wisdom of crowds in Wikipedia: quality through coordination ( https://dl.acm.org/doi/abs/10.1145/1460563.1460572 ) ". Mako was also on the panel, and in his discussion he pointed out the same thing that impressed me from Nikki's talk. Nikki showed how the concepts of implicit and explicit coordination he and Kraut introduced in 2008 for understanding Wikipedia are useful for designing tools that use AI to support collaborative workflows in ways that just prompting a chatbot or agent can't achieve. The more general answer, which I find inspiring, is that CSCW has built a rich base of concepts that can be productively applied to create new understandings of how AI can be designed, built, and used collaboratively. Nikki's talk showed how engaging concepts from CSCW's legacy can lead to novel research ideas, and I think such scholarship has a disciplinary character that can earn respect and distinction in a way that bandwagoning rarely does. Highlights from paper sessions Here are a few paper presentations by people outside CDSC we thought wroth highlighting. There's one pick from each of us who attended. I (Nate) have lightly edited the others' descriptions. Nate's pick: People Can Accurately Predict Behavior of Complex Algorithms That Are Available, Compact, and Aligned by Lindsay Popowski, Helena Vasconcelos, Ignacio Javier Fernandez Heinsen, Chijioke Mgbahurike, Ralf Herbrich, Jeff Hancock, and Michael S. Bernstein. https://doi.org/10.1145/3788067 This paper's title is a great description of the findings and central contribution. The problem of designing algorithmic systems to make them less opaque and confusing is usually framed as making AI "explainable" or "interpretable". This framing centers the model and seemingly constrains the solution space to the problem of making the inner workings of complex mathematical models comprehensible to end users. I love how this paper reframes this problem from computational complexity to cognitive complexity in terms of a user's ability to construct a valid intuition for the model's behavior. Then they show that this sort of problem, which also seems closer to what many use cases actually need, is solvable by models that are good at one comprehensible and useful thing. This is a really cool example of positivist HCI research that conceives a theory by drawing from HCI and cognitive science and then tests it in a straightforward experiment. Kaylea's pick: The Persistence of Retracted Papers on Wikipedia by Haohan Shi, Yulin Yu, Daniel Romero, and Emőke-Ágnes Horvát https://doi.org/10.1145/3817014 Kaylea wrote: It takes a (very) long time for retracted papers to get removed from Wikipedia, and the problem is worse for highly-cited papers but better for open access papers. I suspect that journals and academics can do more to set the record straight when retractions happen. Mako's pick: Creating Group Rules with AI: Human-AI Collaboration in WhatsApp Moderation by Gauri Nayak, Farhana Shahid, Kiran Garimella, and Aditya Vashistha. https://doi.org/10.1145/3816915. Mako wrote: A speculative design paper that worked with 20 WhatsApp admins to use an AI to generate rules. It's an interesting experiment that I think challenges some things the CDSC work on rules has taken for granted and that uses methods extremely different from those we would use to approach the problems. The work points to a range of interesting future research directions for rule researchers. Yiwei's pick: The Activist’s Guide to the Decentralized Social Universe by Sybille Légitime and Harini Suresh. https://doi.org/10.1145/3817010 Yiwei wrote: I like how the authors of this paper take platform choice as a question of collective action, showing that leaving a platform only works if communities can find somewhere that fits their specific threats and resources. Add a comment to this post: https://blog.communitydata.science/report-back-from-cscw-2026/#respond -- Manage Subscriptions https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email… Unsubscribe: https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email…

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The Politics of the “Non-Political”
by Community Data Science Collective 12 Oct '26

12 Oct '26

Post : The Politics of the “Non-Political” URL : https://blog.communitydata.science/the-politics-of-the-non-political/ Posted : October 12, 2026 at 09:25 Author : Yibin Fan Categories : Papers, Publications Communication around politics matters a lot for the healthy development of a society. We usually associate political information with campaigns, public appearances by politicians, and discussions about voting. Yet politically relevant information nowadays frequently enters everyday life: when people decide which city or neighborhood to live in, when groups gather around sharply different cultures, and even when people date each other. These everyday connections are at the heart of our new article, “The Politics of the ‘Non-Political’: A Conceptual Review ( https://doi.org/10.1080/10584609.2026.2745844 ) ”, published in Political Communication. My co-author Yufan Guo ( https://www.linkedin.com/in/yufan-guo-817625378/ ) , a PhD student in Communication at the Chinese University of Hong Kong, and I (Yibin Fan ( https://www.yibinfan.cc/ ) ) set out to understand how researchers conceptualize the relationship between politics and what they call “non-political.” The rapid development of media technologies further blurs these boundaries. On social media, for instance, you cannot always prevent yourself from encountering political videos or advertisements, even when you go online for something entirely different. This keeps pushing social scientists to ask: is politics necessarily bounded by political institutions? And when we look beyond those institutions, what on earth counts as political or nonpolitical? Scholarly interest in these questions has grown alongside their presence in everyday life. As the figure below shows, the number of articles in political science and communication with relevant terms roughly tripled over the past two decades. Yet beneath this growing interest, we found surprising inconsistency in how the term is conceptualized, often without a clear definition of either side of the boundary. https://blog.communitydata.science/wp-content/uploads/sites/5/2026/10/pub_c… Amazed, while also puzzled, by this trend in both everyday life and academia, we began reading relevant articles. We started with political science and communication, and followed the question into other fields, which we have found in information science, sociology, and management. Along the way, we encountered studies asking, “What does ‘political’ mean to you? ( https://link.springer.com/article/10.1007/s11109-012-9212-2 ) ” We read about social movement organizers strategically politicizing or depoliticizing their identities ( https://www.tandfonline.com/doi/full/10.1080/14742837.2019.1631153 ) , and about political discussion flourishing in communities around The Bachelor ( https://doi.org/10.1177/14614448221099180 ) , the popular American reality TV show—just to name a few. As we read more, we settled on a scope: empirical studies published in SSCI-indexed political science and communication journals that included “non-political” in their titles, abstracts, or keywords. This gave us 140 articles to review. This is certainly not a perfect way to capture every relevant study. But we believe that explicitly using the term signals an intentional effort to conceptualize the nonpolitical—or, more specifically, to understand politics through its relationship with something considered nonpolitical. Across these articles, we identified eight types of nonpolitical entities. Some concern actors, such as social media influencers and opinion leaders; identities, including religious and gender identities and politicians’ personal identities; issues, such as sexual violence and technology; and content, including memes, everyday posts, and sports news. Others concern media channels, such as Google Play and entertainment communities; social contexts, including dating and social relationships; collective action, such as environmental protests and silence; and cognition, including anger and the desire to emigrate. The range itself was striking: “nonpolitical” could describe a person, a platform, a feeling, or a form of action. We further identified two salient approaches to conceptualizing the nonpolitical. The first is categorical. Researchers treat the political and nonpolitical as distinct categories, comparing them or tracing spillovers between them—for example, how engagement with nonpolitical content might affect political attitudes. The second is contextual. Researchers understand the political and nonpolitical as embedded in one another, with their relationship depending on the setting. Something understood as nonpolitical may become political, or vice versa, through processes of politicization and depoliticization. The following figure illustrates these different ways of relating the two. https://blog.communitydata.science/wp-content/uploads/sites/5/2026/10/conce… Finally, we asked why these relational modes exist at all, and why they take such varied forms. In the studies we reviewed, the nonpolitical almost always helped researchers better understand or articulate the nature of politics. Drawing a boundary between the two also has a long history in Western philosophical traditions. But researchers do not all draw that boundary in the same way. We believe these differences reflect several influences: institutional or relational views of politics, post-positivist or interpretive and critical theoretical orientations, methodological considerations, and rhetorical tensions in how scholars frame their arguments. For us, this review responds to both empirical realities and scholarly debates about the relationship between politics and the nonpolitical in communication processes. It brings together a growing body of research while also inviting reflection on the nature of politics itself. We thus suggest that (de)politicization can offer a sharp conceptual perspective for future research. It directs attention to how these boundaries are constructed, challenged, and changed. It also invites us to think critically about power: who gets to define something as political or nonpolitical, and what follows from that definition? This article also grew through many conversations. I presented our very initial findings and groupings in a graduate seminar on the social construction of news at UW Communication and at the annual retreat of our Community Data Science Collective (CDSC). I was amazed by the positive feedback. Many of us shared a sense that political polarization was becoming visible across more areas of social and public life, which made these questions feel especially relevant. That reception motivated us to develop the review further and present it as a poster at ICA 2025. There, I spoke with at least 30 people interested in the study. Those conversations helped us see how the questions resonated across different research interests. Publishing this conceptual review in Political Communication, as a team consisting of just two doctoral students, makes the experience especially meaningful to us. We are grateful to the journal’s editors and reviewers for their thoughtful work, and to everyone who offered feedback along the way. All of these conversations helped make this article possible. Add a comment to this post: https://blog.communitydata.science/the-politics-of-the-non-political/#respo… -- Manage Subscriptions https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email… Unsubscribe: https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email…

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CDSC at CSCW 2026: Rules, Knowledge Gaps, and AI in Open Source
by Community Data Science Collective 06 Oct '26

06 Oct '26

Post : CDSC at CSCW 2026: Rules, Knowledge Gaps, and AI in Open Source URL : https://blog.communitydata.science/cdsc-at-cscw-2026-rules-knowledge-gaps-a… Posted : October 6, 2026 at 08:08 Author : Benjamin Mako Hill Categories : Conferences and Presentations, Papers The Community Data Science Collective is heading to CSCW 2026 ( https://cscw.acm.org/2026/ ) in Salt Lake City, Utah, October 10–14. Mako Hill, Kaylea Champion, Nate TeBlunthuis, and Yiwei Wu will be there. We hope you’ll join us at any of the sessions below. https://blog.communitydata.science/wp-content/uploads/sites/5/2026/10/cscw2… Tuesday, October 13, 2:30 pm (Skylight Ballroom, Crowdsourcing & Peer Production) Nate TeBlunthuis will present “The Relational Origins of Rules in Online Communities,” a paper with an all-CDSC author list of Charles Kiene, Sohyeon Hwang, Carl Colglazier, Nathan TeBlunthuis, Aaron Shaw, and Benjamin Mako Hill. Although Charles Kiene sadly won't be there to present it, the paper reflects his excellent dissertation work ( https://digital.lib.washington.edu/researchworks/items/e4c3e4d8-c8be-4273-8… ) . (full paper ( https://doi.org/10.1145/3817015 ) ) In the same session, Leah Ajmani will present “Sanctioned by Others: Remediating Knowledge Exclusion on Wikipedia Through Design” by Leah Ajmani, Moyan Zhou, Tanja Andic, Amber Berson, Isaac Johnson, Benjamin Mako Hill, Rebecca Maung, Sneha Narayan, Sarah Severson, Loren Terveen, and Stevie Chancellor. The paper received a DEI Recognition. (full paper ( https://doi.org/10.1145/3816994 ) ) Wednesday, October 14, 9:00 am (Salon E, Decentralized Social Media) Yiwei Wu will present “AI Didn’t Start the Fire: Examining the Stack Exchange Moderator and Contributor Strike” by Yiwei Wu, Leah Ajmani, Nathan TeBlunthuis, and Hanlin Li. (blog post ( https://blog.communitydata.science/ai-didnt-start-the-fire-how-stack-exchan… ) , full paper ( https://doi.org/10.1145/3788040 ) ) The same session will also have “Understanding Community-Level Blocklists in Decentralized Social Media” by Owen Xingjian Zhang, Sohyeon Hwang (CDSC alum and affiliate), Yuhan Liu, Manoel Horta Ribeiro, and Andrés Monroy-Hernández (CDSC affiliate). (full paper ( https://doi.org/10.1145/3817026 ) ) Wednesday, October 14, 11:00 am (Salon D, Lasting Impact Award) Benjamin Mako Hill will give a talk in the Lasting Impact Award session honoring Aniket Kittur and Robert Kraut’s now-classic CSCW 2008 paper, “Harnessing the wisdom of crowds in Wikipedia: Quality through coordination.” Saturday, October 10, 9:00 am–5:30 pm (Snowbird) Beyond the main conference, Matt Gaughan, Kaylea Champion, and Benjamin Mako Hill are co-organizing the workshop Beyond Productivity: AI, Community, and Sustainability in Open Source Software ( https://wiki.communitydata.science/OSS_AI_Workshop_(CSCW_2026) ) with Eli Min, Hana Frluckaj, Kevin Crowston, and James Howison. The workshop looks at how generative AI and agentic coding are changing newcomer participation, maintainer burden, trust, and sustainability in open source communities. We look forward to meeting you all in person at CSCW! Add a comment to this post: https://blog.communitydata.science/cdsc-at-cscw-2026-rules-knowledge-gaps-a… -- Manage Subscriptions https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email… Unsubscribe: https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email…

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We’re hiring! Join the CDSC as a Program Coordinator
by Community Data Science Collective 05 Oct '26

05 Oct '26

Post : We’re hiring! Join the CDSC as a Program Coordinator URL : https://blog.communitydata.science/were-hiring-join-the-cdsc-as-a-program-c… Posted : October 5, 2026 at 07:00 Author : Aaron Shaw Categories : Join CDSC, Reflections Come join us and maybe watch the sunrise over Lake Michigan! Do you care about community, design, computing, and research? We are hiring a program coordinator ( https://careers.northwestern.edu/psc/hrnu_er/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HR… ) to grow the public impact of the Community Data Science Collective (CDSC) ( https://communitydata.science ) and Northwestern University Center for Human Computer Interaction +Design (HCI+D) ( https://hci.northwestern.edu ) . The person in this role will work across both groups, focusing on outreach and communications, managing social media and web content, promoting research and activities to internal and external audiences, building research communities, strategic event planning, and supporting program administration for both the CDSC and HCI+D. The position is full time and based in Evanston on the Northwestern University campus (although a portion of the work may be done remotely). The average salary for similar positions at Northwestern is around $55,000 per year and includes benefits (compensation details for this position can only be determined by Northwestern HR in the hiring process). The position is available as a 2-year term-limited role, with the possibility of additional years depending on available funding. Details regarding specific responsibilities, duties, minimum qualifications, and competencies are available via the job posting on the Northwestern HR website ( https://careers.northwestern.edu/psc/hrnu_er/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HR… ) . About Northwestern’s Center for HCI+Design and the Community Data Science Collective The Community Data Science Collective ( https://communitydata.science ) is an interdisciplinary research group made up of faculty, students, and affiliates ( https://communitydata.science/People ) mainly at the University of Washington Department of Communication, the Northwestern University Department of Communication Studies, the Carleton College Computer Science Department, the iSchool at the University of Texas at Austin, and the Purdue University School of Communication. To learn more about the Community Data Science Collective, you should check out our wiki ( https://communitydata.science ) , blog ( https://blog.communitydata.science ) , and recent publications ( https://communitydata.science/Publications ) . Northwestern’s Center for Human Computer Interaction + Design ( https://hci.northwestern.edu ) brings together researchers and practitioners from across the university to study, design, and develop the future of human and computer interaction at home, work, and play. The center draws upon Northwestern’s pioneering leadership in interaction and design research, and supports researchers in their pursuit of new interaction paradigms to support a collaborative, sustainable, and equitable society. Contact Please contact Aaron Shaw ( mailto:aaronshaw@northwestern.edu ) with questions. Both the CDSC and the Center for HCI+D are committed to creating diverse, inclusive, equitable, and accessible environments. We actively work to maintain an open community where each person’s experiences, backgrounds, and perspectives are valued and encouraged. We look forward to working with someone who shares these values. Ready to apply? Please apply via the Northwestern University job posting ( https://careers.northwestern.edu/psc/hrnu_er/EMPLOYEE/HRMS/c/HRS_HRAM_FL.HR… ) (and note that the job ID is 54580). We will begin reviewing applications immediately (continuing on a rolling basis until the position is filled). Add a comment to this post: https://blog.communitydata.science/were-hiring-join-the-cdsc-as-a-program-c… -- Manage Subscriptions https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email… Unsubscribe: https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email…

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Prospective PhD Student Q&A – October 2, 2026
by Community Data Science Collective 17 Sep '26

17 Sep '26

Post : Prospective PhD Student Q&A – October 2, 2026 URL : https://blog.communitydata.science/prospective-phd-student-qa-october-2-202… Posted : September 17, 2026 at 06:15 Author : Jeremy Foote Categories : Uncategorized Thinking about applying to graduate school? Wonder what it’s like to pursue a PhD or research-based master's degree? Interested in understanding relationships between technology and society? Curious about how to do research on online communities like Reddit, Wikipedia, or GNU/Linux? The Community Data Science Collective ( https://wiki.communitydata.science/Main_Page ) is hosting a virtual Q&A session on Friday, October 2 at 12 pm PT / 2pm CT / 3pm ET for prospective students. This session is scheduled for an hour and will be divided between a larger group session with faculty and smaller groups with current graduate students. If you would like to attend, register at this link ( https://docs.google.com/forms/d/e/1FAIpQLScKyB5pUYMNy85txxdtovL312OEri2S6zM… ) ! This post provides a very brief rundown on the CDSC, the different universities and PhD and research master's programs our faculty members are affiliated with, and some general ideas about what we’re looking for when we review applications. What is the Community Data Science Collective? The Community Data Science Collective ( http://wiki.communitydata.science/ ) (or CDSC) is a joint research group of (mostly quantitative) empirical social scientists and designers pursuing research about the organization of online communities, peer production, and learning and collaboration in social computing systems. We are based at Northwestern University ( http://nortwhestern.edu/ ) , the University of Washington ( http://washington.edu/ ) -Seattle, University of Washington-Bothell ( https://www.uwb.edu ) , The University of Texas at Austin ( https://www.utexas.edu/ ) , Purdue University ( http://purdue.edu/ ) , and a few other places. You can read more about us and our work on our research group blog ( http://blog.communitydata.science/ ) and on the collective’s website/wiki ( http://wiki.communitydata.science/ ) . What are these different Ph.D. programs? Why would I choose one over the other? This year the group includes multiple faculty principal investigators (PIs) who are actively recruiting graduate students: Kaylea Champion ( https://kayleachampion.com/ ) (University of Washington in Bothell), Nathan TeBlunthuis ( https://teblunthuis.cc/ ) (University of Texas at Austin), Jeremy Foote ( https://jeremydfoote.com/ ) (Purdue University), ( http://aaronshaw.org/ ) Benjamin Mako Hill ( http://mako.cc/academic ) (University of Washington in Seattle), Aaron Shaw ( http://aaronshaw.org/ ) (Northwestern University). Each of these PIs advises PhD and/or M.S. students in graduate programs at their respective universities. We also have one faculty PI who is not currently recruiting students, but is an active member of the group: Ryan Funkhouser (University of Idaho). Our programs are each described below. Although we often work together on research and serve as co-advisors on students' projects, each faculty member has specific areas of expertise and interests. The reasons you might choose to apply to one of these PhD or M.S. programs or to work with a specific faculty member could include factors like your previous training, career goals, and the alignment of your specific research interests with our respective skills. At the same time, a great thing about the CDSC is that we all collaborate and regularly co-advise students across our campuses, so applying to or attending one program does not prevent you from accessing the expertise of our whole group. But please keep in mind that our different PhD and M.S. programs have different application deadlines, requirements, and procedures! Faculty who are actively recruiting PhD Students this year If you are interested in applying to any of the programs, we strongly encourage you to reach out to the specific faculty in that program before submitting an application. https://blog.communitydata.science/wp-content/uploads/sites/5/2024/10/favor… Nathan TeBlunthuis, Ventrait Pictures Nathan TeBlunthuis ( https://teblunthuis.cc/ ) is an Assistant Professor in the School of Information at the University of Texas at Austin ( https://ischool.utexas.edu/ ) in the area of social informatics ( https://www.ischool.utexas.edu/programs/informatics/curriculum/social-infor… ) . Nathan’s research focuses on analyzing ecosystems of online communities ( https://ojs.aaai.org/index.php/ICWSM/article/view/19352/19124 ) , AI tools in peer production ( https://dl.acm.org/doi/abs/10.1145/3449130 ) , and methods in computational social science ( https://doi.org/10.1080/19312458.2023.2293713 ) . His current projects continue in these areas and also draw from them all to understand how information sources achieve legitimacy in online communities. He works primarily using computational tools and big data, but also grounds his work in qualitative evidence. https://blog.communitydata.science/wp-content/uploads/sites/5/2026/09/bio-p… Jeremy Foote Jeremy Foote ( http://jeremydfoote.com/ ) is an Assistant Professor at the Brian Lamb School of Communication at Purdue University ( https://www.cla.purdue.edu/academic/communication/ ) . He is affiliated with the Organizational Communication and Media, Technology, and Society programs. Jeremy’s research focuses on how individuals decide when and in what ways to participate in online communities, how communities change the people who participate in them, and how both of those processes can help us to understand what people believe and which things become popular and influential. He and his students use multiple methods, including data science, agent-based modeling, field experiments, and interviews. https://blog.communitydata.science/wp-content/uploads/sites/5/2026/09/mako_… Benjamin Mako Hill, Photo by Pedro Pacheco ( https://commons.wikimedia.org/wiki/File:Benjamin_Mako_Hill_portrait_at_Wiki… ) Benjamin Mako Hill ( http://mako.cc/academic ) is an Associate Professor of Communication at the University of Washington. He is also adjunct faculty at UW’s Department of Human-Centered Design and Engineering (HCDE), Computer Science and Engineering (CSE), and the Information School. Although many of Mako’s students are in the Department of Communication ( http://www.com.washington.edu/ ) , he has also advised students in all three other departments—although he typically has more limited ability to admit students into those programs on his own and usually does so with a co-advisor in those departments. Mako’s research focuses on population-level studies of peer production projects, computational social science, efforts to democratize data science, and informal learning. Mako has also put together a webpage for prospective graduate students ( https://wiki.communitydata.science/User:Benjamin_Mako_Hill/Prospective_grad… ) with some useful links and information. https://blog.communitydata.science/wp-content/uploads/sites/5/2025/09/image… Aaron Shaw, Nikki Ritcher Photography Aaron Shaw ( http://aaronshaw.org/ ) is a Professor in the Department of Communication Studies at Northwestern ( http://www.communication.northwestern.edu/communicationstudies/ ) . In terms of PhD programs, Aaron’s primary affiliations are with the Media, Technology and Society (MTS) ( http://mts.northwestern.edu/ ) and the Technology and Social Behavior (TSB) ( http://tsb.northwestern.edu/ ) Ph.D. programs (please note: the TSB program is a joint degree between Communication and Computer Science). Aaron also has a courtesy appointment in the Sociology Department ( http://sociology.northwestern.edu/ ) at Northwestern, but he has not directly supervised any Ph.D. advisees in that department (yet). Aaron studies organizing, participation, and governance in online communities, especially ones that create public information resources and digital infrastructure. Aaron’s current projects focus on comparative analysis of the organization of peer production communities, online community governance, LLM-based social science, and AI's impacts on digital public infrastructure. Faculty who Supervise ADMITTED M.S. and B.S. Students https://blog.communitydata.science/wp-content/uploads/sites/5/2025/09/small… Kaylea Champion Kaylea Champion ( https://kayleachampion.com/ ) is an Assistant Professor in Computing & Software Systems ( https://www.uwb.edu/stem/about/divisions/css ) at the University of Washington-Bothell ( https://www.uwb.edu/ ) . Kaylea’s research investigates how people collaborate to build digital infrastructure, including operating systems, programming languages, and information repositories. What gets made and maintained and secured—and what gets neglected? What risks do we face (including from AI and cybercriminals)? What practices lead to better outcomes? How can we work smarter and what can we stop doing? Kaylea's work seeks to bridge the divide between research and practice, which for her means building relationships with practitioner communities, organizations, and industry to directly share research findings. If you are interested in the Computing & Software Systems graduate programs at the University of Washington - Bothell, you should register for one of the information sessions specific to these programs ( https://graduate.uwb.edu/portal/stem-css-info-session ) as well. Kaylea's department only admits M.S. and B.S. students (MS-Cybersecurity and MS-Computer Science and Software Engineering). In addition, she is happy to support any students who are working with others in the CDSC and can serve on thesis and dissertation committees. Other Faculty members of the CDSC Ryan Funkhouser Ryan Funkhouser ( https://www.linkedin.com/in/ryan-funkhouser-phd-b28020116/ ) is an Assistant Professor in the Department of Psychology and Communication at the University of Idaho ( https://catalog.uidaho.edu/colleges-related-units/letters-arts-social-scien… ) . Ryan’s research focuses on communication processes for bridging ideological divides in online spaces. His work includes explorations of deliberation-focused online communities, the role of narrative in persuasion, and the mechanisms of belief change. Ryan utilizes both computational and qualitative methods to explore text data, primarily from online sources. What do you look for in PhD applicants? There’s no easy or singular answer to this. In general, we look for curious, intelligent people driven to develop original research projects that advance scientific and practical understanding of topics that intersect with any of our collective research interests. To get an idea of the interests and experiences present in the group, read our respective bios and CVs (follow the links above to our personal websites). Specific skills we regularly use include consuming and producing social science and/or social computing (human-computer interaction) research; applied statistics and statistical computing; various empirical research methods; social theory and cultural studies; and more. Formal qualifications that speak to similar skills and show up in your resume, transcripts, or work history are great, but we are much more interested in your capacity to learn, think, write, analyze, and/or code effectively than in your credentials, test scores, grades, or previous affiliations. It’s graduate school, after all, and we do not expect you to show up knowing how to do all the things already. Intellectual creativity, persistence, and a willingness to acquire new skills and problem-solving matter a lot. We think doctoral education is less about executing tasks someone else hands you and more about learning to identify a new, important problem; develop an appropriate approach to solving it; and explain all of the above and why it matters so others can learn from you in the future. Evidence that you can or at least want to do these things is critical. Indications that you can also play well with others and would make a generous, friendly colleague are really important too. All of this is to say, we do not have any one trait or skill set we look for in prospective students. We strive to be inclusive along every possible dimension. Each person who has joined our group has contributed unique skills and experiences, as well as personal interests. We want our future students and colleagues to do the same. Now what? Still not sure whether or how your interests might fit with the group? Still have questions? Still reading and just don’t want to stop? Follow the links above for more information. Feel free to email at least one of us. We are happy to answer your questions and always eager to chat. https://blog.communitydata.science/wp-content/uploads/sites/5/2022/04/478px… Add a comment to this post: https://blog.communitydata.science/prospective-phd-student-qa-october-2-202… -- Manage Subscriptions https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email… Unsubscribe: https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email…

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Community Dialogue: Social Drivers of Online Hate
by Community Data Science Collective 15 Sep '26

15 Sep '26

Post : Community Dialogue: Social Drivers of Online Hate URL : https://blog.communitydata.science/community-dialogue-social-drivers-of-onl… Posted : September 15, 2026 at 10:13 Author : Jeremy Foote Categories : Uncategorized Toxicity, aggression, racism, misogyny, and other forms of hate are unfortunately common in online spaces. Researchers have often treated those who engage in online hate as social deviants, enabled to act out by the affordances of online anonymity. This Friday we will be hosting two speakers who will discuss an emerging perspective that sees online hate as a social process, where those who engage in hate do so for social approval, often as part of (anti)social organizations. Dyuti Jha ( https://sites.google.com/view/dyutijha/home ) (Fort Hays State University ) will discuss how users engage in online hate as a form of hybrid social action. Although online hate has been conceptualized as a malicious form of individual expression or dyadic interactions, this research explores the way in which users develop collective identities from their membership in online communities of hate, connect with each other based on shared grievances, and engage in expressions of online hate as a social action motivated by moral outrage and the need for social approval. Using AI-facilitated qualitative conversational data collection, her work demonstrates that online hate campaigns are organized as both collective and connective action, with hidden organizing providing support for "grassroots" connective spread of hate campaigns. This research offers useful perspectives to understand the motivations and the organizing strategies of concealed actors behind the execution and sustenance of online hate campaigns. Joe Walther ( https://www.comm.ucsb.edu/people/joe-walther ) (UC Santa Barbara) will discuss how conventional research and activism about online hate in social media presumes that its purpose is to antagonize victims. A new approach argues that hate is primarily for haters, and that the incentive for online hate posting is the social approval its providers glean from admirers. This presentation outlines social approval theory, growing empirical evidence supporting and challenging its propositions, and implications for deterrence. Speaker Bios: * Joe Walther holds the Bertelsen Presidential Chair in Technology and Society at the University of California, Santa Barbara, where he is a Distinguished Professor of Communication. He is also a faculty associate at the Berkman Klein Center for Internet & Society at Harvard University. His theoretical and empirical work focus on interpersonal and intergroup communication in mediated interaction, from the development of relationships to the propagation of online hate. Social Processes of Online Hate ( https://doi.org/10.4324/9781003472148 ) (co-edited with R. Rice, Routledge 2025) is available open access. * Dyuti Jha is an Assistant Professor of Organizational Communication at Fort Hays State University. Using experiments and AI facilitated conversations, her doctoral dissertation studied the impact and social organization of online hate. Her other research interests are individual and organizational resilience and online toxicity's effect on political expression on the internet. This event is organized by the CDSC and hosted and supported, in part, by a National Science Foundation grant (IIS-2045055) so that it will be held at no cost to attendees. A code of conduct will be shared with participants prior to the event. Discussions will be held under Chatham House Rule. Presentations will be recorded, though discussions will not. Register to Attend The event will be held on Friday, September 18 from 3pm - 5pm Eastern Time. To get to know a bit more about the audience, we ask you to fill out this very brief ( https://docs.google.com/forms/d/e/1FAIpQLSfVpOZuQUVskkf7TMUUrF-YgcZU9Mk7_Yl… ) survey in order to register. ( https://docs.google.com/forms/d/e/1FAIpQLSfVpOZuQUVskkf7TMUUrF-YgcZU9Mk7_Yl… ) Those who register to attend will be sent a meeting invite with a link to the Zoom room. What is a Dialogue? The Science of Community Dialogue Series ( https://wiki.communitydata.science/Dialogues ) is a series of conversations between researchers, experts, community organizers, and other people who are interested in how communities work, collaborate, and succeed. To learn more, watch this short introduction video with Aaron Shaw ( https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=1bb154… ) . Add a comment to this post: https://blog.communitydata.science/community-dialogue-social-drivers-of-onl… -- Manage Subscriptions https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email… Unsubscribe: https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email…

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Seeking to Interview People Who Make Software!
by Community Data Science Collective 08 Jul '26

08 Jul '26

Post : Seeking to Interview People Who Make Software! URL : https://blog.communitydata.science/seeking-to-interview-people-who-make-sof… Posted : July 8, 2026 at 15:25 Author : kaylea Categories : Uncategorized Students in the CDSC are recruiting for two interview studies. The AI Slop study seeks to interview people involved in open source software who have experience dealing with AI-authored contributions in open source. We hope to learn more about how communities are responding to this challenge. You can read more about the study and fill out our screening survey here! ( https://wiki.communitydata.science/Slop_study ) The Software Handoffs study seeks to interview people about how responsibility for a given piece of code gets handed off from one person to the next. We are wondering how this task is handled in industry and how this might differ from what is taught in a computer science curriculum. You can read more about the study and fill out our screening survey here! ( https://wiki.communitydata.science/Handoff_study ) Add a comment to this post: https://blog.communitydata.science/seeking-to-interview-people-who-make-sof… -- Manage Subscriptions https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email… Unsubscribe: https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email…

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Impacts of AI on Software Engineering Processes
by Community Data Science Collective 01 Jul '26

01 Jul '26

Post : Impacts of AI on Software Engineering Processes URL : https://blog.communitydata.science/impacts-of-ai-on-software-engineering-pr… Posted : July 1, 2026 at 15:24 Author : kaylea Categories : Celebrations How does software engineering change when AI is part of the product we're creating? Current practice suggests a need for structured experimentation, tolerance for uncertainty, deep qualitative research and evaluation, wrangling with questions of meaning and knowledge, advanced statistics and mathematics, and more. How might we expand our efforts to build these skills? CDSC faculty member Kaylea Champion recently received the very welcome news that, together with her Co-PI Jeffrey Kim, she was awarded a grant from the UW's internal AI-SEED program to explore this key topic in empirical software engineering and computer-supported cooperative work! The official press release from UW -- including many other exciting awards supporting innovation in teaching with / about AI -- is here ( https://www.ai.uw.edu/aiuw-awards-36-seed-ai-grants-in-its-inaugural-fundin… ) . Grant Title: "Rethinking engineering workflows: Building AI-powered software." Grant abstract: "This project focuses on teaching students the impacts to a software engineering workflow -- including planning and estimation, requirements analysis, design, development, testing, deployment and maintenance -- when AI-powered features are part of the product. Although substantial attention has been paid to AI as a code generating tool and to the technical skills involved in building AI models, impacts of AI features on overall engineering workflow is relatively less explored. All computing students should have an awareness of these process impacts, regardless of their specialties and goals. We propose to develop and evaluate two interventions: a no-code hands-on simulation of evaluating and fine-tuning a model, and a series of enhancements and extensions for learning modules focused on different stages of a development project. We propose to develop a preliminary version of these interventions, then to evaluate and refine them through a series of co-design workshops, and finally to publish our results." Add a comment to this post: https://blog.communitydata.science/impacts-of-ai-on-software-engineering-pr… -- Manage Subscriptions https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email… Unsubscribe: https://subscribe.wordpress.com/?key=65cad9df3c24375c969692300da5e2ea&email…

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