AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Over twenty editions, the ICWSM community has examined social life online as platforms, interactions, and research methods have changed. What can this body of research tell us at this critical juncture, as AI increasingly reshapes how people communicate online? We analyzed 2,139 indexed contributions from 2007 to 2026,...
Online communities are valued not only for answers, but for the diversity of experiences and perspectives they contain. Generative search increasingly mediates access to this discourse, yet little is known about which community voices survive retrieval and synthesis. We audit Reddit Answers using 10,000 queries from 20...
A randomized vignette experiment with 285 U.S. adults across eight financial decisions independently varying three advice styles---AI, expert, and online community---and displayed source labels while holding the underlying recommendation consistent found expert-style advice remained most preferred when shown without so...
AI companions can purportedly adopt racial personas, raising questions about how they represent identity and how users interpret these portrayals. We combined an algorithmic audit of race-coded AI personas with interviews with 12 companion users who interacted with a probe. Our audit revealed systematic differences, su...
This work presents the first large-scale empirical comparison of AI-agent and human online communities, analyzing 73,899 Moltbook and 189,838 Reddit posts across five matched communities.
The Positive Queue is introduced as a positive counterpart to Reddit's modqueue: a dedicated space for moderators to discover contributions and behaviors they want to encourage and positively reinforce, and conceptualize positive moderation as recognition infrastructure that shapes what moderators notice, whose judgmen...
It was found that both AI summaries and user reviews influenced participants' opinions, with negative summaries having a larger effect than positive ones and negative summaries having a larger effect than positive ones.
PeerPen, a writing assistance tool embedded within a Reddit-like interface, supporting two main features: draft generation and revision of user-written responses, is built and it is found that PeerPen reduced the burden of composing responses and increased confidence in offering support.
The findings suggest that open-source models, when trained with community-derived preference signals, can support high-quality mental health support assistance while offering a more privacy-preserving alternative for sensitive support contexts.
It is shown that this handoff step is a structural source of privacy leakage: summaries preferentially preserve operational facts while weakening the boundary metadata that governs how those facts may be used---a failure mode the authors call summary collapse.
It is suggested that local preference recognition requires community-specific training signal, not just better prompting, and this work supports future research on community-aware reward modeling, feed curation, and positive moderation.
It is found that LLMs outperform expectations at replicating comment structure and formality, but struggle to accurately capture nuanced emotions, e.g. understating joy and overstating anger.
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