# From Web(logs) to Web(AI): Questions, Platforms, and Methods across Twenty Editions of ICWSM

arXiv: https://arxiv.org/abs/2610.00205 · HTML: https://mlsanity.com/paper/2610.00205/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 23 of its 72 references that are in the map.
- First posted on arXiv 20 Sep 2026.

## Builds on (most cited first, 23 of 23)

- [Automated Hate Speech Detection and the Problem of Offensive Language](https://mlsanity.com/paper/1703.04009/) (2017)
- [Measurement and Fairness](https://mlsanity.com/paper/1912.05511/) (2019)
- [The Pushshift Reddit Dataset](https://mlsanity.com/paper/2001.08435/) (2020)
- [Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates](https://mlsanity.com/paper/2005.00649/) (2020)
- [Media Cloud: Massive Open Source Collection of Global News on the Open Web](https://mlsanity.com/paper/2104.03702/) (2021)
- [Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose](https://mlsanity.com/paper/1306.5204/) (2013)
- [Spillover of Antisocial Behavior from Fringe Platforms: The Unintended Consequences of Community Banning](https://mlsanity.com/paper/2209.09803/) (2022)
- [Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference](https://mlsanity.com/paper/2009.09961/) (2020)
- [Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls](https://mlsanity.com/paper/1403.7400/) (2014)
- [Reconsidering Tweets: Intervening During Tweet Creation Decreases Offensive Content](https://mlsanity.com/paper/2112.00773/) (2021)
- [Correcting Sociodemographic Selection Biases for Population Prediction from Social Media](https://mlsanity.com/paper/1911.03855/) (2019)
- ["I Won the Election!": An Empirical Analysis of Soft Moderation Interventions on Twitter](https://mlsanity.com/paper/2101.07183/) (2021)
- [Political Polarization in Online News Consumption](https://mlsanity.com/paper/2104.06481/) (2021)
- [Seeing Like an AI: How LLMs Apply (and Misapply) Wikipedia Neutrality Norms](https://mlsanity.com/paper/2407.04183/) (2024)
- [Stranger Danger! Cross-Community Interactions with Fringe Users Increase the Growth of Fringe Communities on Reddit](https://mlsanity.com/paper/2310.12186/) (2023)
- [Uncovering the Internet's Hidden Values: An Empirical Study of Desirable Behavior Using Highly-Upvoted Content on Reddit](https://mlsanity.com/paper/2410.13036/) (2024)
- [Variation across Scales: Measurement Fidelity under Twitter Data Sampling](https://mlsanity.com/paper/2003.09557/) (2020)
- [The Gray Area: Characterizing Moderator Disagreement on Reddit](https://mlsanity.com/paper/2601.01620/) (2026)
- [Characterizing Collective Attention via Descriptor Context: A Case Study of Public Discussions of Crisis Events](https://mlsanity.com/paper/1909.08784/) (2019)
- [Characterizing Political Campaigning with Lexical Mutants on Indian Social Media](https://mlsanity.com/paper/2401.03533/) (2024)
- [Cascade-based Randomization for Inferring Causal Effects under Diffusion Interference](https://mlsanity.com/paper/2405.12340/) (2024)
- [Reddit Rules and Rulers: Quantifying the Link Between Rules and Perceptions of Governance across Thousands of Communities](https://mlsanity.com/paper/2501.14163/) (2025)
- [WEIRD ICWSM: How Western, Educated, Industrialized, Rich, and Democratic is Social Computing Research?](https://mlsanity.com/paper/2406.02090/) (2024)

## Abstract (arXiv)

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, distinguishing topics identified through nonnegative matrix factorization from problem framings captured through explicit textual cues. We find that platform mentions shift from blogs toward Twitter and, more recently, Reddit. Online community research maintains a similar topic share (10.5% to 10.0%), but governance cues within it increase from 4.0% to 34.3%. Harm-related cues also increase after restricting abstracts to a fixed length. Our review also traces advances in sampling, measurement, and causal and experimental methods. We discuss how AI-mediated interactions complicate these questions and provide a reporting checklist to support research across changing platforms.