Decentralizing Social Media: The challenges and opportunities of federated systems

A Virtual Thought Leader Dialogue on May 23, from 4 – 5:15 p.m. CST. Register here to join.

Based on File:Decentralization.jpg, by Adam Aladdin, CC-BY-SA 3.0

How can we create more trustworthy and accountable social media that support diverse communities? Decentralized social media—systems that allow users to connect and communicate across independent services like Mastodon or BlueSky—offer promising alternatives to centralized commercial platforms like Instagram, TikTok, or X. However, decentralized social media also face urgent design challenges, especially when it comes to content integrity, protecting community trust and safety, and forging collective governance. What happens when there is no central authority to review posts or ban abusive users? How can networks of autonomous communities build and adopt systems to govern effectively? What critical infrastructure can prevent the pervaisve harms of existing social media and support the integrity of public discourse?

Join Northwestern’s Center for Human-Computer Interaction + Design (HCI+D) and the Community Data Science Collective (CDSC) for an engaging conversation about the challenges and opportunites of decentralized social media on May 23rd from 4 to 5:15 p.m. CST. This panel features designers, leaders, and researchers involved in federated social media and will address opportunities for effective design and governance in this space.

Panelists include Jaz-Michael King, Bryan Newbold, and Christine Lemmer-Webber. Short presentations will be followed by discussion and Q&A moderated by Aaron Shaw (Northwestern HCI+D, CDSC). 

Moderator: Aaron Shaw, photograph by Nikki Ritcher Photography

Aaron Shaw is Associate Professor of Communication Studies and Sociology (by courtesy) at Northwestern University and a Faculty Associate of the Berkman Klein Center for Internet and Society at Harvard University. He is a co-founder of the Community Data Science Collective. At Northwestern, he is also affiliated with the Center for Human-Computer Interaction + Design (HCI+D), the Institute for Policy Research, the Buffett Institute for Global Affairs, and the Public Affairs Residential College.

Speaker: Christine Lemmer-Webber, Executive Director of Spritely Networked Communities Institute

Christine has devoted her life to advancing user freedom. Realizing that the federated social web was fractured by a variety of incompatible protocols, she co-authored and shepherded ActivityPub‘s standardization. She has also contributed to many other free and open source projects, including co-founding MediaGoblin.

Christine established the open source Spritely Project to solve known problems in existing centralized and decentralized social media platforms and to re-imagine the way we build networked applications – work that now continues here at the institute under her guidance as Executive Director.

Speaker: Jaz-Michael King, Executive Director of IFTAS (Federated Trust & Safety)

An accomplished professional with an extraordinary record of enabling data-driven decisions, developing innovative products, creating new business opportunities, driving strong operational performance, and building high-performing, agile teams.
Highly versatile, with extensive experience in data and technology from a privacy, improvement, and reporting perspective, Jaz has a proven record in building solutions for non-profit programs. 
As Executive Director of IFTAS, Jaz is now focused on independent, open Social Web activities, with the aim of creating #BetterSocialMedia by supporting trust and safety at scale in federated social media networks.

Speaker: Bryan Newbold, Protocol Engineer at BlueSky

Bryan works at Bluesky, a startup company building a federated social media protocol called “atproto”. Until a few months ago he worked at the Internet Archive collecting scientific research datasets and publications, and created And before that he worked on infrastructure at Stripe, attended the Recurse Center in New York City, and built Atomic Magnetometers for a small New Jersey company called Twinleaf.

Over that same time period, Bryan climbed up and down the ladder of abstraction, obtaining an undergraduate degree in physics (at MIT), operating under-ice robots in Antarctica, developing open hardware lab instrumentation for large-scale brain probing (at LeafLabs), cataloging hundreds of millions of electronics components (at Octopart), and improved production service reliability at Stripe (a financial infrastructure start-up).

Bryan is a transplant from the East Coast and enjoys the road biking, large trees, generous salads, used bookstores, and world-class tech non-profits. This will be his third year serving on the Code of Conduct team at DWeb Camp.

Interested in attending? Register here to join!

Adopting “third-party” end-user bots for managing online communities on platforms

A screenshot of the configuration panel for Moderator functions of a popular end-user bot called Dyno, adopted by millions of communities on Discord.

Bots made by end users are crucial to the success of online communities, helping community leaders moderate content as well as manage membership and engagement. But most folks don’t have the resources to develop custom bots and turn to existing bots shared by their peers. For example, on Discord, some especially popular bots are adopted by millions of communities. However, because these bots are ultimately third-party tools — made by neither the platform nor the community leader in question — they still come with several challenges. In particular, community leaders need to develop the right understandings about a bot’s nature, value, and use in order to adopt it into their community’s existing processes and culture.

In organizational research, these “understandings” are sometimes described as technological frames, a concept developed by Orlikowski & Gash (1994) as they studied why technologies became used in unexpected ways in organizational settings. When your technological frames are well-aligned with a tool’s design, you can imagine that it is easier to assess whether that tool will be useful and can be smoothly incorporated into your organization as intended. In the context of online communities, well-aligned frames can not only reduce the labor and time of bot adoption, but also help community leaders anticipate issues that might cause harm to the community. Our new paper looks to communities on Discord and asks: How do community leaders shift their technology frames of third-party bots and leverage them to address community needs?

Emergent social ecosystems around bot adoption

Our study interviewed 16 community leaders on Discord, walking through their experiences adopting third-party bots for their communities. These interviews underscore how community leaders have developed social ecosystems around bots: organic user-to-user networks of resources, aid, and knowledge about bots across communities.

Despite the decentralized arrangement of communities on Discord, users devised and took advantage of formal and informal opportunities to revise their understandings about bots, both supporting and constraining how bots became used. This was particularly important because third-party bots pose heightened uncertainties about their reliability and security, especially for bots used to protect the community from external threads (such as scammers). For example, interviewees laid out concerns about whether a bot developer could be trusted to keep their bot online, to respond to problems users had, and to manage sensitive information. The emergent social ecosystems helped users get recommendations from others, assess the reputation of bot developers, and consider whether the bot was a good fit for them along much more nuanced dimensions (in the case of one interviewee, the values of the bot developer mattered as well). They also created opportunities for people to directly get help in setting up bots and troubleshooting them, such as via engaged discussions with other users who had more experience.

Our findings underscore a couple of core reasons why we should care about these social ecosystems:

  1. Closing gaps in bot-related skills and knowledge. Across interviews, we saw patterns of people leveraging the resources and aid in social ecosystems to move towards using more powerful but complex bots. Ultimately, people with diverse technical backgrounds (including those who stated they had no technical background) were able to adopt and use bots — even bots involving code-like configurations in markdown languages that might normally pose barriers. We suggest that the diffusion of end-user tools on social platforms be matched with efforts to provide bottom-up social scaffoldings that support exploration, learning, and user discussion of those tools.
  2. Changing perceptions of the labor involved in bot adoption. The process of bot adoption as a deeply social one appeared to impact how people saw the labor they invested into it, shifting it into something fun and satisfying. Bot adoption was both collaborative, involving many individuals as a user discovered, evaluated, set up, and fine-tuned bots; and communal, with community members themselves taking part in some of these steps. We suggest that bot adoption can provide one avenue to deepen community engagement by creating new ways of participating and generating meta discussions about the community, as well as the platform.
  3. Shaping the assumptions around third-party tools. Social ecosystems enabled people to cherry-pick functions across bots, enabling creative wiggle room in curating a set of preferred functions. At the same time, people were constrained by social signals about what bots are and can do, why certain bots are worth adopting, and how the bot is used. For example, people often talked about genres of bots even though no such formal categories existed. We suggest that spaces where leaders from different communities interact with one another to discuss strategies and experiences can be impactful settings for further research, intervention, and design ideas.

Ultimately, the social nature of adopting third-party bots in our interviews offers insight into how we can better support the adoption of valuable user-facing tools across online communities. As online harms become more and more technically sophisticated (e.g., the recent rise of AI-generated disinformation), user-made bots that quickly respond to emerging issues will play an important role in managing communities — and will be even more valuable if they can be shared across communities. Further attention to the dynamics that enable tools to be used across communities with diverse norms and goals will be important as the risks that communities face, and the tools available to them, evolve.

Engage with us!

If you have thoughts, ideas, questions, we are always happy to talk – especially if you think there are community-facing resources we can develop from this work. There are a few ways to engage with us:

  • Drop a comment below this post!
  • Check out the full paper, available ✨ open access ✨ in the ACM Digital Library.
  • Come by the talks we’ll be giving:
    • at ICA2024 on Saturday, June 22, 2024 in the “Digital Networks, Platforms, and Organizing” session at 3:00-4:15PM in Coolangatta 4 (Star L3);
    • at CSCW2024 in November; schedule is still forthcoming!
  • Connect with us on social media or via email.

Come see us at CHI 2024!

We’re going to be at CHI! The Community Date Science Collective will be presenting work from group members and affiliates. CHI is taking place in Honolulu, Hawaiʻi from May 11th – 16th.

By Robert Linsdell from St. Andrews, Canada – Flight from Honolulu to Hilo. Over Sand Island and Honolulu (503729), CC BY 2.0

Jeremy Foote (Purdue University) coauthored “How Founder Motivations, Goals, and Actions Influence Early Trajectories of Online Communities” with Sanjay R Kairam. This work will be presented at “Online Communities: Engagement A” on Tuesday, May 14th at 9:45 a.m. You can also read about Jeremy and Sanjay’s work on our blog.

Carolyn Zou (Northwestern University) will be presenting with coauthor Helena Vasconcelos on their work “Validation Without Ground Truth? Methods for Trusts in Generative Simulations” at the CHI workshops HEAL (Human-Centered Evaluation and Auditing of Language Models) and TREW (Trust and Reliance in Evolving Human-AI Workflows). They will be presenting posters at both sessions and have been selected as a highlighted paper for HEAL and will be giving a presentation on Sunday, May 12th.

Ruijia Cheng (University of Washington) will be their presenting their research on “AXNav: Replaying Accessibility Tests from Natural Language” with cowriters Maryam Taeb, Eldon Schoop, Yue Jiang, Amanda Swearngin, and Jeffrey Nichols. This presentation will be taking place at “Universal Accessibility” on Tuesday, May 14th at 4:30 p.m.

CDSC affiliate Nicholas Vincent is receiving the Outstanding Dissertation Award for their research on “Economic Concentration and Dispossessive Data Use: Can HCI Solve Challenges from and to AI?“. Nicholas will also be presenting their papers “Pika: Empowering Non-Programmers to Author Executable Governance Policies in Online Communities” with Leijie Wang, Julija Rukanskaitė, and Amy X. Zhang at “Supporting Communities” on Thursday, May 16th at 11:00 a.m. and “A Canary in the AI Coal Mine: American Jews May Be Disproportionately Harmed by Intellectual Property Dispossession in Large Language Model Training” with Heila Precel, Brent Hecht, and Allison McDonald at “Politics of Data” on Wednesday, May 15th at 2:45 p.m.

Mandi Cai (Northwestern University) received an honorable mention award alongside coauthor Matthew Kay for their paper “Watching the Election Sausage Get Made: How Data Journalists Visualize the Vote Counting Process in U.S. Elections“. Mandi will be presenting this research at “Governance and Public Policies” on Wednesday, May 15th at 12:00 p.m.

Founders’ influence on their new online communities

Hundreds of new subreddits are created every day, but most of them go nowhere, and never receive more than a few posts or comments. On the other hand, some become wildly popular. If we want to figure out what helps some things to get attention, then looking at new and small online communities is a great place to start. Indeed, the whole focus of my dissertation was trying to understand who started new communities, and why. So, I was super excited when Sanjay Kairam at Reddit told me that Reddit was interested in studying founders of new subreddits!

The research that Sanjay and I (but mostly Sanjay!) did was accepted at CHI 2024, a leading conference for human-computer interaction research. The goal of the research is to understand 1) founders’ motivations for starting new subreddits, 2) founders’ goals for their communities, 3) founders’ plans for making their community successful, and 4) how all of these relate to what happens to a community in the first month of its existence. To figure this out, we surveyed nearly 1,000 redditors one week after they created a new subreddit.

Lots of Motivations and Goals

So, what did we learn? First, that founders have diverse motivations, but the most common is interest in the topic. As shown in the figure above, most founders reported being motivated by topic engagement, information exchange, and connecting with others, while self-promotion was much more rare.

When we asked about their goals for the community, founders were split, and each of the options we gave was ranked as a top goal by a good chunk of participants. While there is some nuance between the different versions of success, we grouped them into “quantity-oriented” and “quality-oriented”, and looked at how motivations related to goals. Somewhat unsurprisingly, folks interested in self-promotion had quantity-oriented goals, while those interested in exchanging information were more focused on quality.

Diversity in plans

We then asked founders about what plans they had for building their community, based on recommendations from the online community literature, such as raising awareness, welcoming newcomers, encouraging contributions, and regulating bad behavior. Surprisingly, for each activity, about half of people said they planned to engage in doing that thing.

Early Community Outcomes

So, how do these motivations, goals, and plans relate to community outcomes? We looked at the first 28 days of each founded subreddit, and counted the number of visitors, number of contributors, and number of subscribers. We then ran regression analyses analyzing how well each aspect of motivations, goals, and plans predicted each outcome. High-level results and regression tables are shown below. For each row, when β is positive, that means that the given feature has a positive relationship with the given outcome. The exponentiated rate ratio (RR) column provides a point estimate of the effect size. For example, Self-Promotion has an RR of 1.32, meaning that if a given person’s self-promotion motivation was one unit higher the model predicts that their community would receive 32% more visitors.

A number of motivations predicted each of the outcomes we measured. The only consistently positive predictor was topical interest. Those who started a community because of interest in a topic had more visitors, more contributors, and more subscribers than others. Interestingly, those motivated by self-promotion had more visitors, but fewer contributors and subscribers.

Goals had a less pronounced relationship with outcomes. Those with quality-oriented goals had more contributors but fewer visitors than those with quantity-oriented goals. There was no significant difference in subscribers for founders with different types of goals.

Finally, raising awareness was the strategy most associated with our success metrics, predicting all three of them. Surprisingly, encouraging contributions was associated with more contributors, but fewer visitors. While we don’t know the mechanism for sure, asking for contributions seems to provide a barrier that discourages newcomers from taking interest in a community.

So what?

We think that there are some key takeaways for platform designers and those starting new communities. Sanjay outlined many of them on the Reddit engineering blog, but I’ll recap a few.

First, topical knowledge and passion is important. This isn’t a causal study, so we don’t know the mechanisms for sure, but people who are passionate about a topic may be aware of other communities in the space and are able to find the right niche; they are also probably better at writing the kinds of welcome messages, initial posts, etc. that appeal to people interested in the topic.

Second, our work is yet more evidence that communities require different things at different points in their lifecycle. Founders should probably focus on building awareness at first, and worry less about encouraging contributions or regulating behavior.

Finally, we think there are a lot of opportunities for designers to take diverse motivations and goals seriously. This could include matching people by their motivations for using a community, developing dashboards that capture different aspects of success and community health and quality, etc.

Learn More

If you want to learn more about the paper, you have options!

CDSC welcomes Madison Deyo!

Madison Deyo has recently joined the CDSC as a Program Coordinator and we couldn’t be more thrilled to welcome her to the team!

Madison Deyo headshot.

Madison is based at Northwestern. With the CDSC, Madison’s role includes a mix of event planning and coordination; outreach and communications; and supporting the operations of the group. She also works with the Northwestern Center for Human-Computer Interaction + Design. Madison brings experience working with community-based non-profits in several different capacities.

Madison currently lives in Chicago, and grew up in Wisconsin, where she attended the University of Wisconsin-Madison. There, she received my B.S. in Art (with a focus on illustration) and Communications: Radio-TV-Film. In addition to her position at Northwestern, Madison also works as a freelance artist designing mead labels, tattoos, and occasionally album/EP covers. You can check out her portfolio.

Replication data release for examining how rules and rule-making across Wikipedias evolve over time

Screenshot of the same rule, Neutral Point of View, on five different language editions. Notably, the pages are different because they exist as connected but ultimately separate pages.

While Wikipedia is famous for its encyclopedic content, it may be surprising to realize that a whole other set of pages on Wikipedia help guide and govern the creation of the peer-produced encyclopedia. These pages extensively describe processes, rules, principles, and technical features of creating, coordinating, and organizing on Wikipedia. Because of the success of Wikipedia, these pages have provided valuable insights into how platforms might decentralize and facilitate participation in online governance. However, each language edition of Wikipedia has a unique set of such pages governing it respectively, even though they are part of the same overarching project: in other words, an under-explored opportunity to understand how governance operates across diverse groups.

In a manuscript published at ICWSM2022, we present descriptive analyses examining on rules and rule-making across language editions of Wikipedia motivated by questions like:

What happens when communities are both relatively autonomous but within a shared system? Given that they’re aligned in key ways, how do their rules and rule-making develop over time? What can patterns in governance work tell us about how communities are converging or diverging over time?

We’ve been very fortunate to share this work with the Wikimedia community since publishing the paper, such as the Wikipedia Signpost and Wikimedia Research Showcase. At the end of last year, we published the replication data and files on Dataverse after addressing a data processing issue we caught earlier in the year (fortunately, it didn’t affect the results – but yet another reminder to quadruple-check one’s data pipeline!). In the spirit of sharing the work more broadly since the Dataverse release, we summarize some of the key aspects of the work here.

Study design

In the project, we examined the five largest language editions of Wikipedia as distinct editing communities: English, German, Spanish, French and Japanese. After manually constructing lists of rules per wiki (resulting in 780 pages), we took advantage of two features on Wikipedia: the revision histories, which log every edit to every page; and the interlanguage links, which connect conceptually equivalent pages across language editions. We then conducted a series of analyses examining comparisons across and relationships between language editions.

Shared patterns across communities

Across communities, we observed that trends suggested that rule-making often became less open over time:

Figure 2 from the ICWSM paper
  • Most rules are created early in the life of the language edition community’s life. Over a nearly 20 year period, roughly 50-80% of the rules (depending on the language edition) were created within the first five years!
  • The median edit count to rule pages peaked in early years (between years 3 and 5) before tapering down. The percent of revisions dedicated to editing the actual rule text versus discussing it shifts towards discussion of rule across communities. These both suggest that rules across communities have calcified over time.

Said simply, these communities have very similar trends in rule-making towards formalization.

Divergence vs convergence in rules

Wikipedia’s interlanguage link (ILL) feature, as mentioned above, lets us explore how the rules being created and edited on communities relate to one another. While the trends above highlight similarities in rule-making, here, the picture about how the rule sets are similar or not is a bit more complicated.

On one hand, the top panel here shows that over time, all five communities see an increase in the proportion of rules in their rules sets that are unique to them individually. On the other hand, the bottom panel shows that editing efforts concentrate on rules that are more shared across communities.

Altogether, we see that communities sharing goals, technology, and a lot more develop substantial and sustained institutional variations; but it’s possible that broad, widely-shared rules created early may help keep them relatively aligned.

Key takeaways

Investigating governance across groups like Wikipedia is valuable for at least two reasons.

First, an enormous amount of effort has gone into studying governance on English Wikipedia, the largest and oldest language edition, to distill lessons about how we can meaningfully decentralize governance in online spaces. But, as prior work [e.g., 1] shows, language editions are often non-aligned in both the content they produce and how they organize that content. Some early stage work we did noted this held true for rule pages on the five language editions of Wikipedia explored here. In recent years, the Wikimedia Foundation itself has made several calls to understand dynamics and patterns beyond English Wikipedia. This work is in part in response to this movement.

Second, the questions explored in our work highlight a key tension in online governance today. While online communities are relatively autonomous entities, they often exist within social and technical systems that put them in relation with one another – whether directly or not. Effectively addressing concerns about online governance means understanding how distinct spaces online govern in ways that are similar or dissimilar, overlap or conflict, diverge and converge. Wikipedia can offer many lessons to this end because it has an especially decentralized and participatory vision of how to govern itself online, such as how patterns of formalization impact success and engagement. Future work we are working on continues in this vein – stay tuned!

Sources of Underproduction in Open Source Software

Although the world relies on free/libre open source software (FLOSS) for essential digital infrastructure such as the web and cloud, the software that supports that infrastructure are not always as high quality as we might hope, given our level of reliance on them. How can we find this misalignment of quality and importance (or underproduction) before it causes major failures?

How can we find misalignment of quality and importance (underproduction) before it causes major failures?

In previous work, we found that underproduction is widespread in packages maintained by the Debian community, and when we shared this work in the Debian and FLOSS community, developers suggested that the age and language of the packages might be a factor, and tech managers suggested looking at the teams doing the maintenance work. Software engineering literature had found some support for these suspicions as well, and we embarked on a study to dig deeper into some of the factors associated with underproduction.

Our study was able to partially confirm this perspective using the underproduction analysis dataset from our previous study: software risk due to underproduction increases with age of both the package and its language, although many older packages and those written in older languages are and continue to be very well-maintained.

In this plot, dots represent software packages and their age, with higher underproduction factor indicating higher risk. The blue line is a smoothed average: note that we see an increase over time initially, but the trend flattens out for older packages.

This plot shows the spread of the data across the range of underproduction factor, grouped by language, where higher values are indications of higher risk. Languages are sorted from oldest on the left (Lisp) to youngest on the right (Java). Although newer languages overall are associated with lower risk, we see a great deal of variation.

However, we found the resource question more complex: additional contributors were associated with higher risk instead of decreasing it as we hypothesized. We also found that underproduction is associated with higher eigenvector centrality in the network formed if we take packages as nodes and edges by having shared maintainers; that is, underproduced packages were likely to be maintained by the same people maintaining other parts of Debian, and not isolated efforts. This suggests that these high-risk packages are drawing from the same resource pool as those which are performing well. A lack of turnover in maintainership and being maintained by a team were not statistically significant once we included maintainer network structure and age in our model.

How should software communities respond? Underproduction appears in part to be associated with age, meaning that all communities sooner or later may need to confront it, and new projects should be thoughtful about using older languages. Distributions and upstream project developers are all part of the supply chain and have a role to play in the work of preventing and countering underproduction. Our findings about resources and organizational structure suggest that “more eyeballs” alone are not the answer: supporting key resources may be of particular value as a means to counter underproduction.

This paper will be presented as part of the International Conference on Software Analysis, Evolution and Reengineering (SANER) 2024 in Rovaniemi, Finland. Preprint available HERE; code and data released HERE.

This work would not have been possible without the generosity of the Debian community. We are indebted to these volunteers who, in addition to producing Free/Libre Open Source Software software, have also made their records available to the public. We also gratefully acknowledge support from the Sloan Foundation through the Ford/Sloan Digital Infrastructure Initiative, Sloan Award 2018-11356 as well as the National Science Foundation (Grant IIS-2045055). This work was conducted using the Hyak supercomputer at the University of Washington as well as research computing resources at Northwestern University.

FLOSS project risk and community formality

What structure and rules are best for communities producing high-quality free/libre and open source software (FLOSS)? The stakes are high: cybersecurity researchers are raising the alarm about cybersecurity risk due to undermaintained components in the global software supply chain—much of which is FLOSS. In work that’s just been accepted to the IEEE International Conference on Software Analysis, Evolution and Reengineering (‘SANER’), we studied 182 Python-language packages in the GNU/Linux Debian distribution, examining the relationship between their levels of engineering formality and software risk. We found that more formal developer organization is associated with higher levels of software risk, and more widely spread developer responsibility is associated with lower levels of software risk.

We studied software risk through the underproduction metric initially developed by Champion and Hill (2021). Underproduction is a measurement of misalignment between the usage demands of a software project and the contributions of the project’s developer community. As such, underproduction measures the risk that software will be undermaintained, possibly including a security bug.

Our work examines the relationship between risk due to underproduction and governance formality. We employed measures initially developed by Tamburri et al. (2013) and later re-implemented in Tamburri et al. (2019). These metrics use multiple measures of software project formality — such as the average contributor type, usage of GitHub milestones, and age — to evaluate how formally structured a given project is.

Plot of the relationship between mean underproduction factor and mean membership type (MMT), a metric encapsulating the diffusion of merge responsibility across a project’s developer community.

We used linear regression to conclude that more formal project structures are associated with higher levels of underproduction and thus, increased project risk. We also found that the share of community-members who have merged code into the main development branch is also related to underproduction, with lower levels of underproduction correlated with larger shares of community mergers.

Evaluated together, these two conclusions suggest that operating less formally and sharing power more equally is associated with lower underproduction risk. The development of FLOSS project engineering is a process laden with tradeoffs, we hope that our conclusions can help better inform community decision making and organization.

For more details, visualizations, statistics, and more, we hope you’ll take a look at our paper. If you are attending SANER in March 2024, we hope you’ll talk to us in Rovaniemi, Finland!


The full citation for the paper is:

Gaughan, Matthew, Champion, Kaylea, and & Hwang, Sohyeon. (2024) “Engineering Formality and Software Risk in Debian Python Packages.” In 31st IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER2024) (Short Paper and Posters Track). Rovaniemi, Finland.

We have also released replication materials for the paper, including all the data and code used to conduct the analyses.

This blog post and the paper it describes are collaborative work by Matt Gaughan, Kaylea Champion, and Sohyeon Hwang.

A new paper on the risk of nationalist governance capture in self-governed Wikipedia projects

Wikipedia is one of the most visited websites in the world and the largest online repository of human knowledge. It is also both a target of and a defense against misinformation, disinformation, and other forms of online information manipulation. Importantly, its 300 language editions are self-governed—i.e., they set most of their rules and policies. Our new paper asks: What types of governance arrangements make some self-governed online groups more vulnerable to disinformation campaigns? We answer this question by comparing two Wikipedia language editions—Croatian and Serbian Wikipedia. Despite relying on common software and being situated in a common sociolinguistic environment, these communities differed in how successfully they responded to disinformation-related threats.

For nearly a decade, the Croatian language version of Wikipedia was run by a cabal of far-right nationalists who edited articles in ways that promoted fringe political ideas and involved cases of historical revisionism related to the Ustaše regime, a fascist movement that ruled the Nazi puppet state called the Independent State of Croatia during World War II. This cabal seized complete control of the governance of the encyclopedia, banned and blocked those who disagreed with them, and operated a network of fake accounts to give the appearance of grassroots support for their policies.

Thankfully, Croatian Wikipedia appears to be an outlier. Though both the Croatian and Serbian language editions have been documented to contain nationalist bias and historical revisionism, Croatian Wikipedia alone seems to have succumbed to governance capture: a takeover of the project’s mechanisms and institutions of governance by a small group of users.

The situation in Croatian Wikipedia was well-documented and is now largely fixed, but still know very little about why Croatian Wikipedia was taken over, while other language editions seem to have rebuffed similar capture attempts. In a new paper that is accepted for publication in the Proceedings of the ACM: Human-Computer Interaction (CSCW), we present an interview-based study that tries to explain why Croatian was captured while several other editions facing similar contexts and threats fared better.

Short video presentation of the work given at Wikimania in August 2023.

We interviewed 15 participants from both the Croatian and Serbian Wikipedia projects, as well as the broader Wikimedia movement. Based on insights from these interviews, we arrived at three propositions that, together, help explain why Croatian Wikipedia succumbed to capture while Serbian Wikipedia did not: 

  1. Perceived Value as a Target. Is the project worth expending the effort to capture?
  2. Bureaucratic Openness. How easy is it for contributors outside the core founding team to ascend to local governance positions?
  3. Institutional Formalization. To what degree does the project prefer personalistic, informal forms of organization over formal ones?
The conceptual model from our paper, visualizing possible institutional configurations among Wikipedia projects that affect the risk of governance capture. 

We found that both Croatian Wikipedia and Serbian Wikipedia were attractive targets for far-right nationalist capture due to their sizable readership and resonance with a national identity. However, we also found that the two projects diverged early on in their trajectories in terms of how open they remained to new contributors ascending to local governance positions and the degree to which they privileged informal relationships over formal rules and processes as organizing principles of the project. Ultimately, Croatian’s relative lack of bureaucratic openness and rules constraining administrator behavior created a window of opportunity for a motivated contingent of editors to seize control of the governance mechanisms of the project. 

Though our empirical setting was Wikipedia, our theoretical model may offer insight into the challenges faced by self-governed online communities more broadly. As interest in decentralized alternatives to Facebook and X (formerly Twitter) grows, communities on these sites will likely face similar threats from motivated actors. Understanding the vulnerabilities inherent in these self-governing systems is crucial to building resilient defenses against threats like disinformation. 

For more details on our findings, take a look at the preprint of our paper.

Preprint on The paper has been accepted for publication in Proceedings of the ACM on Human-Computer Interaction (CSCW) and will be presented at CSCW in 2024. This blog post and the paper it describes are collaborative work by Zarine Kharazian, Benjamin Mako Hill, and Kate Starbird.

New year, new job with us? CDSC is hiring!

Do you care about community, design, computing, and research? We are looking for a person to grow the public impact of the Community Data Science Collective (CDSC) and Northwestern University Center for Human Computer Interaction +Design (HCI+D). We are hiring a full time Program Coordinator to work in both groups. This person will focus on outreach, communications, research community development, strategic event planning, and administration for both the CDSC and HCI+D.

Although a portion of the work may be done remotely, attendance for in-person meetings and workshops is required and the position is located in Evanston on the Northwestern University campus. The average salary for similar positions at Northwestern is around $55,000 per year and includes excellent benefits (compensation details for this position can only be determined by Northwestern HR in the hiring process). We’re looking for a minimum 2 year commitment.


These fall into four categories, with specific examples in each listed below:

  1. Outreach & communications
    • Manage social media posting (LinkedIn, Mastodon, X, WordPress etc.)
    • Post events to listservs and websites
    • Advertise events such as the Collective’s “Science of Community” series and the Center’s “Thought Leader Dialogues”
    • Build contact-lists around specific events and topics
    • Share messages with internal and external audiences
  2. Research community development
    • Recruit participants to community events
    • Organize group retreats (3-4 year total)
    • Engage with community members of both the Collective and Center
  3. Strategic event planning
    • Develop and execute a strategic event plan for in-person/virtual events
    • Collaborate with Collective and Center members to plan and recruit speakers for events
  4. Administration:
    • Schedule and plan research meetings
    • Track and report on collective and center achievements
    • Draft annual research and donor reports
    • Document processes and initiatives

Core competencies:

  • Ability to use and learn web content management tools, such as wordpress, and wikis.
  • General organization
  • Communication (be clear, be concise)
  • Meeting facilitation
  • Managing upwards
  • Small/medium scale (20-50 people) event planning
  • Creative thinking and problem solving


Candidates must hold at least a bachelor’s degree. Familiarity with event planning, community management, project management, and/or scientific research is a plus, as is prior experience in the social or computer sciences, research organizations, online communities, and/or public interest technology and advocacy projects of any kind.

About Northwestern’s Center for HCI+Design and the Community Data Science Collective

The Community Data Science Collective is an interdisciplinary research group made up of faculty, students, and affiliates mainly at the University of Washington Department of Communication, the Northwestern University Department of Communication Studies, the Carleton College Computer Science Department, and the Purdue University School of Communication. To learn more about the Community Data Science Collective, you should check out our wiki, blog, and recent publications.

Northwestern’s Center for Human Computer Interaction + Design is an interdisciplinary research center that 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 in the pursuit of new interaction paradigms to support a collaborative, sustainable, and equitable society.


Please contact Aaron Shaw with questions. Both the CDSC and the Center for HCI+D are committed to creating diverse, inclusive, equitable, and accessible environments and we look forward to working with someone who shares these values.

Ready to apply?

Please apply via the Northwestern University job posting (and note that the job ID is 49284). We will begin reviewing applications immediately (continuing on a rolling basis until the position is filled).

(revised to fix a broken link)