Ozgur Can Seckin
@ozgurcanseckin.bsky.social
100 followers 83 following 28 posts
Indiana University Bloomington - Informatics PhD. previously: Plaid MLE, Glassdoor MLE, Sabanci University - Data Science MSc., Galatasaray University - Economics BSc.
Posts Media Videos Starter Packs
ozgurcanseckin.bsky.social
Thank you for the article! AI "resonating" with people has been another problem we should definitely think more of www.nytimes.com/2025/08/08/t...
Chatbots Can Go Into a Delusional Spiral. Here’s How It Happens.
www.nytimes.com
ozgurcanseckin.bsky.social
Kudos to my wonderful advisors and coworker who made this paper possible! @baottruong.bsky.social @alessandroflammini @fil.bsky.social 🙏
ozgurcanseckin.bsky.social
We propose that "constructive conflicts" can model healthier, "bridging" content 🌉 But, “destructive conflicts" shouldn't be ignored but approached with careful linguistic choices to transform toxic arguments into productive dialogues.
ozgurcanseckin.bsky.social
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
ozgurcanseckin.bsky.social
- 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.
ozgurcanseckin.bsky.social
To identify constructive conflict, we train two models to score posts based on their likelihood of attracting toxic comments - which we call toxicity attraction (TA) model - and their controversiality - (C) model 💻 Plotting the scores inferred by these models shows clear patterns.
ozgurcanseckin.bsky.social
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.
ozgurcanseckin.bsky.social
In our research, we argue that the key lies in identifying constructive conflict — controversial posts that are toxicity resilient. We define a "toxicity resilient" post as one that is less likely to attract toxic responses from other users. See our #ICWSM2026 paper here arxiv.org/abs/2509.18303 📖
Identifying Constructive Conflict in Online Discussions through Controversial yet Toxicity Resilient Posts
Bridging content that brings together individuals with opposing viewpoints on social media remains elusive, overshadowed by echo chambers and toxic exchanges. We propose that algorithmic curation coul...
arxiv.org
ozgurcanseckin.bsky.social
A simple solution, prioritizing only “the feel-good" content, is flawed, as it avoids important societal topics that are inherently negative and can devolve into toxic debates. After all, how often does thinking about wars, viruses, or economic policy put a smile on your face?
ozgurcanseckin.bsky.social
Modern social media is divisive, partly due to recommender algorithms that promote emotionally charged, negative content at the expense of thoughtful discourse. Researchers are exploring prosocial recommenders that foster positive outcomes, aiming for users to feel connected rather than angry 💡
ozgurcanseckin.bsky.social
#ic2s2 let's connect! If we had a conversation and I haven't followed you yet, please do follow!
ozgurcanseckin.bsky.social
@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!
Reposted by Ozgur Can Seckin
baottruong.bsky.social
The Effects of Outgroup Agreement and Ingroup Dissent on Political Polarization
📍 Talk | Jul 24, 11:00 AM | Troselli

Scaling of Community Rules Across Mastodon Servers
📍 Talk | Jul 24, 11:00 AM | Vingen 3+4
#ic2s2
Reposted by Ozgur Can Seckin
baottruong.bsky.social
In Norrköping for #IC2S2!
Excited to share three work with my amazing collaborators @dowonkim.bsky.social , @ozgurcanseckin.bsky.social, and @rasikamurali.bsky.social — come say hi!

🧵 Where to find us:
Predicting Constructive Conflict in Online Discussions
📍 Poster | Jul 23, 1:30 PM | Atrium
Reposted by Ozgur Can Seckin
osome.iu.edu
Our team just launched three new tools to help you explore social media data:
🌉NewsBridge – Adds AI-powered context to Facebook posts
🔍 Barney’s Tavern – Search 34B social media posts
🌐 OSoMeNet – Visualize how info spreads across platforms
Learn more and try them out:
osome.iu.edu/research/blo...
Three New Tools to Explore Social Media
The Observatory on Social Media (OSoMe, pronounced “awesome”) is excited to introduce three new tools that will make it easier to study and engage with...
osome.iu.edu
Reposted by Ozgur Can Seckin
fil.bsky.social
… And the winners of the Spring 2025 NaN/CNetS/OSoMe Foosball Tournament are… Akanksha and Dimitri (double) and @ozgurcanseckin.bsky.social (single). Congratulations!!! 🏆
ozgurcanseckin.bsky.social
Hi Jaycee, The plots reflect numbers for all users - we haven’t distinguished between bots and real people.

Though, given that generative AI can now create highly realistic personas and images, it seems like there’s a growing need for a sophisticated bot detection algorithm to catch bots online..
ozgurcanseckin.bsky.social
All is done by my wonderful co-authors and advisors here! @filipisilva.bsky.social, @baottruong.bsky.social, Sangyeon Kim, Fan Huang, Nick Liu, Alessandro Flammini, @fil.bsky.social, @osome.iu.edu
ozgurcanseckin.bsky.social
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.
ozgurcanseckin.bsky.social
All is done by my wonderful co-authors here! @filipisilva.bsky.social @baottruong.bsky.social @sangyeonkim @fanhuang.bsky.social @nickliu @alessandroflammini @fil.bsky.social
ozgurcanseckin.bsky.social
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.
ozgurcanseckin.bsky.social
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).
ozgurcanseckin.bsky.social
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.
ozgurcanseckin.bsky.social
Paper alert! 🚨 We investigate Bluesky’s journey from an invitation only platform with a few thousands of users to reaching 30 million users in terms of user activity and network growth.

📄 Full paper: arxiv.org/abs/2504.12902
💻 Codes: github.com/osome-iu/ris...
💾 Dataset: zenodo.org/records/1506...