Since destructive conflicts are too important to ignore, we analyze their language 🔍 We find that how something is said matters immensely. Civil language (asking questions, providing detail, and using hedges) makes posts far more resilient to toxicity, while negative language has the opposite effect

- Destructive conflicts 🪖 (high C & high TA, panel c) focus on polarizing identity issues like abortion and LGBTQ+ rights.
- Constructive conflicts 🕊️ (high C & low TA, panel d) spark civil debate on policy topics like student loans, AI, and marijuana legalization.

We find that a post doesn't need to be toxic to attract toxic comments ☢️ Our Reddit data shows that 47% of non-toxic submissions still attract at least one toxic reply, while only 6% of toxic submissions do. The initial post's content, therefore, is a poor predictor of a comment section's health.

@ic2s2.bsky.social 2025 was amazing! Thanks to all the committee members for organizing.

I had a chance to present my recent work, met some brilliant people, got star struck a few times, had great feedback, experienced Sweden, and got to catch up with my academic father :) couldn't ask for more!

As Bluesky continues to mature, influential accounts are emerging, posing familiar risks of misinformation, abuse and toxicity on platform. Understanding these dynamics can help inform effective governance and moderation strategies moving forward. Toxic posts: >.5 score from OpenAI moderation endp.

Our analysis reveals that Bluesky rapidly developed a dense, highly clustered network structure. This "friend-of-a-friend" connectivity, characterized by strong hubs, enables swift and viral information diffusion, similar to established platforms such as Twitter/X and Weibo.

Despite initial bursts and declines in total and average activity, Bluesky achieved a stable level of daily engagement, with around 15% active users after the US Elections, matching inactivity rates on X/Twitter (~85% lurkers).

Bluesky's growth was driven by key events: the public access launch, Brazil's ban on X, X's block policy change, and the US elections. Each event triggered significant user migrations and formed distinct communities.

To advance the study of IOs and improve their detection, we present new, anonymized datasets encompassing both IO and control data drawn from 26 distinct, verified campaigns in multiple countries.

Over the past decade, social media platforms have shifted from serving primarily as open information channels to becoming vulnerable conduits for orchestrated manipulation, known as information operations (IOs).