Online discourse surrounding geopolitical crises is volatile and complex. For example, users can often change their opinions, and apply rationales divergently based on the specific scenario under discussion. This paper explores such stance and rationale divergence in social media discussions. We focus on two major ongoing conflicts: the Russia-Ukraine and Israel-Palestine wars. Through this, we identify a set of users who discuss both conflicts, and then label each user’s comments with their stance and associated rationale. Using this unique dataset, we explore how people apply rationales divergently, and evolve their opinions over time. Our research contributes to the CHI community by providing a reusable, rationale-level annotation methodology. Our findings can inform the design of moderation tools, recommender systems, and discussion interfaces. These can be used to surface disagreements, calibrate echo-chamber exposure, and ultimately foster healthier online discourse.

Archive of Our Own (AO3) is a prominent fanfiction platform widely recognized for its feminist design ethos, with a commitment to inclusive, pluralism and community-driven content creation. Among the content on it, Real Person Fiction (RPF) — creations based on public figures rather than fictional characters — offers a unique lens into how users engage with identity, visibility, and cultural narratives. In this study, we conduct a large-scale computational analysis to examine gender representation, thematic diversity, and occupational portrayals. Our findings reveal a significant gender imbalance, with man characters disproportionately over-represented. The readers themselves are also often portrayed as sexual figures. Overall, the relationship portrayals tend to mirror occupational roles, incorporate sexual elements, and reconstruct gender tropes. We interrogate how these patterns intersect with authorship, identity, and power. This work contributes to ongoing conversations about equity, ethics, and feminist values in digital content ecosystems and feminist HCI development.

In today’s digital landscape, the prevalence of sensitive online content has made trigger warnings essential. These warnings inform viewers that the content they are about to see contains sensitive artifacts (e.g. violence). This paper studies the use of trigger warnings, exploiting data from two major platforms: Does the Dog Die, a crowdsourcing trigger warnings platform, and IMDb, a media database. We first study how different media types (e.g. films, video games, and TV shows) are labeled with varying trigger warnings and the different co-occurrence patterns among different trigger warnings. We also discover controversy surrounding certain trigger warnings, with inconsistent opinions stated by different people. We further show that different jurisdictions (e.g. USA vs. UK) assign different content ratings (e.g. R-18) for the same media, even when the same trigger warnings are present. Finally, we develop automatic detectors to identify trigger warnings from IMDb text. We achieve F1 scores exceeding 0.7 for all 10 selected trigger warnings.

The ongoing Russia-Ukraine war has been extensively discussed on social media. One commonly observed problem in such discourse is the emergence of echo chambers, where users are rarely exposed to opinions outside their own worldview. Prior literature on this topic has assumed that such users hold a single consistent view. However, recent work has revealed that complex topics often trigger bipartisanship among certain people. With this in mind, we study the presence of echo chambers on Twitter related to the Russo-Ukrainian war. We measure their presence and identify an important subset of bipartisan users who vary their opinion during the invasion. We then explore the role they play in the communications graph and their impact on echo chambers.