I research online communities and create computational social science tools.
🌐🏳️🌈🤓
| Website | https://carlcolglazier.com/ |
We made a discord for CS/HCI PhD students to meet folks / socialize, and are having a social hour tonight (the 18th) at 7pm EST-whenever.
A bit last minute on hci.social but send folks our way if they are interested!
Our ICWSM paper (with @axz and Tim Althoff) looks at what it actually means to make online communities "better."
Thru surveys of 6k+ redditors ✒️ , we find that while quality and variety of content are generally considered most important, and size and democracy are least important, there is immense variety in values 🌈!
▶️ no one size fits all solution! 🗜️
Moderators think democracy is less important than non-mods, and there is extra disagreement over safety.
Making online social communities 'better' is a challenging undertaking, as online communities are extraordinarily varied in their size, topical focus, and governance. As such, what is valued by one community may not be valued by another. However, community values are challenging to measure as they are rarely explicitly stated. In this work, we measure community values through the first large-scale survey of community values, including 2,769 reddit users in 2,151 unique subreddits. Through a combination of survey responses and a quantitative analysis of public reddit data, we characterize how these values vary within and across communities. Amongst other findings, we show that community members disagree about how safe their communities are, that longstanding communities place 30.1% more importance on trustworthiness than newer communities, and that community moderators want their communities to be 56.7% less democratic than non-moderator community members. These findings have important implications, including suggesting that care must be taken to protect vulnerable community members, and that participatory governance strategies may be difficult to implement. Accurate and scalable modeling of community values enables research and governance which is tuned to each community's different values. To this end, we demonstrate that a small number of automatically quantifiable features capture a significant yet limited amount of the variation in values between communities with a ROC AUC of 0.667 on a binary classification task. However, substantial variation remains, and modeling community values remains an important topic for future work. We make our models and data public to inform community design and governance.
This is a fascinating graph of American attitudes towards science from 1973-2021.
The whole thing is interesting, but look at how the divergence by party starts around 2007, then just takes off.
Computing technology—and AI in particular—now plays a major role in our media system, personalizing content feeds, informing content moderation decisions at scale, automatically generating articles and synthetic media, powering social bots that chat or persuade, and driving myriad other production processes that influence large chunks of what we all pay attention to. Issues ranging from the proliferation of disinformation, to bias in content exposure, online harassment, and the polarization or radicalization of beliefs are crucial to research and address. How can we ensure that this complex media system we all inhabit encourages individuals and society in productive directions, supporting rather than undermining democracy? In this panel, we’ll explore the technology, the issues, and what research, design, practice, and policy can do to work towards a media environment that is healthy for democracy and society. Join us for this important conversation with Chris Bail, Mor Naaman, and Rebekah Tromble in a virtual panel forum moderated by Ágnes Horvát.
Jeffrey P. Bigham 🔥🔥
Andrew Kuznetsov
Galen Weld
Jordan Taylor
Bryan Alexander