Hannah Overbye-Thompson

4. The Oracle of Bacon 🥓🎬
A classic: plug in any actor and see how many steps it takes to reach Kevin Bacon (or any other actor).
Based on co-appearances in films. oracleofbacon.org

3. The Beer Graph 🍺
Curious how Lagers relate to Stouts?
This interactive network lets you explore how beers are connected by taste, aroma, and appearance.
Fun use of similarity graphs!
seekshreyas.github.io/beerviz/

YouTube video by BBC World Service How trees secretly talk to each other - BBC World Service

2. The Hidden Network of Trees 🌳
Trees communicate underground using fungal networks; sharing nutrients, warning of threats, and shaping forest life.
A lovely example of why we study two-mode networks

🍄📡 www.youtube.com/watch?v=DUqE...

In the Network of the Conclave - Bocconi University How network science can help us understand who will be the next Pope. The study by Soda, Iorio, and Rizzo reveals how status, information and alliances influence the papal election.

1. Who Will Be the Next Pope?
Network science can help us predict it.
The Network Conclave project mapped connections between cardinals; before Robert Prevost was selected, we could see he had the highest eigenvector centrality (i.e., he knew important others).
👑🌐 www.unibocconi.it/en/news/netw...

After a great summer teaching Social Networks at UCSB, I wanted to share 4 of my favorite network examples we explored in class 🧪🧵

1. Who Will Be the Next Pope?
2. The Hidden Network of Trees 🌳
3. The Beer Graph 🍺
4. The Oracle of Bacon 🥓🎬

Psychopathology and Gaming Disorder in Adolescents This cohort study uses data from the Adolescent Brain Cognitive Development Study to examine directional longitudinal associations between psychopathology and gaming disorder among adolescents.

jamanetwork.com/journals/jam...

New from @kyliewoodman.bsky.social "baseline levels of psychopathology were significantly associated with an increased risk of developing gaming disorder 1 year later. However, there was no significant association between gaming disorder and the development or worsening of psychopathology." 🧪

Amazing job @kyliewoodman.bsky.social. This is such important research.

Social (media) psychology of the “news-finds-me” perception: habits, mindsets, and beliefs Abstract. Unintended encounters with news on social media can foster a reliance on incidental news exposure and the perception that “news finds me.” Becaus

doi.org/10.1093/jcmc...

New study (Campbell & Hawkins, 2025) examines why people expect news to find them on social media (vs seeking it out). Key finding: when people habitually scroll social media w/out thinking + believe algorithms/lack of control drive SM usage, they're more likely to rely on incidental news exposure 🧪

Taken together, I hope these contributions make it easier to:
• Frame algorithmic bias more clearly
• Talk about how people respond to it in everyday life
• Study that behavior with more precision

Thanks for reading!

5/5 🧵

Finally, the paper offers an example for thinking about when and how to study workarounds to algorithmic bias, depending on whether algorithmic bias is real, perceived, or both, which I hope can serve as a starting point for examining bias in various sociotechnical contexts.

4/5 🧵

The paper proposes the concept of “workarounds” to describe how individuals respond to biased systems. Algorithmic bias workarounds are goal-driven attempts by users to overcome, bypass, or reduce perceived or existing algorithmic bias, which is something we lack consistent language for.

3/5 🧵

One of the challenges I've had when studying the effects of algorithmic bias is getting a high-level picture of how bias enters algorithms. Here I offer a simple breakdown of where/how bias can arise across different stages of development as well as some domains where we commonly see bias

2/5 🧵

Excited to share my new work aimed at making algorithmic bias easier to study w/3 key contributions

• Clear overview of how/where algorithmic bias arises
• Workarounds as a concept for user adaptation
• Framework for analyzing bias that is real, perceived, or absent

1/5 🧵🧪
doi.org/10.1007/s001...

Grist, the evolution of spreadsheets A modern, open source spreadsheet that goes beyond the grid

If you have a job you want to add to the spreadsheet, use this form: docs.getgrist.com/forms/8bZ1HM...

Comm Job Spreadsheet 2025-2026 - Grist A modern, open source spreadsheet that goes beyond the grid

For anyone on the Communication job market this year S. Rutherford McEwan has put together an excellent spreadsheet for 2025-2026 openings. Highly recommend checking it out (whether you're applying or hiring):

docs.getgrist.com/rHppfvPrMDQd...

#commsky #academicsky #communication

Predicting human decisions with behavioural theories and machine learning - Nature Human Behaviour A new model merges behavioural science and machine learning to predict choice under risk and uncertainty. Tested on multiple large datasets, it outperforms top psychological and AI models, enabling ac...

doi.org/10.1038/s415...

Paper by @oriplonsky.bsky.social et al., introduces BEAST-GB, merging behavioral decision theory with XGBoost to predict choices under risk/uncertainty. Key finding: behavioral features are critical even with abundant training data, suggesting theory-guided ML beats purely data-driven approaches 🧪

Deciphering authenticity in the age of AI: how AI-generated disinformation images and AI detection tools influence judgements of authenticity - AI & SOCIETY An ongoing surge of Artificial Intelligence (AI)-enabled false content has been spreading its way through the information ecosystem, including AI-generated images, which have been used as part of poli...

🚨 New publication alert 🚨

Aqsa Farooq and I explore how aesthetic realism and emotional salience influence authenticity judgements of AI-generated disinformation images.

#GenAI #disinformation #authenticity #commsky

link.springer.com/article/10.1...

doi.org/10.1111/ntwe...

New paper by Zhang et al. examines algorithmic management (AM) systems identifying 5 perspectives: surveillance/control, neutral tool, agentic boss, socio-technical process, and contradictory unity. AM creates tensions between control vs autonomy, transparency vs opacity & efficiency vs fairness 🧪

New study (2025) introduces the Capability-Personalization Framework to explain when people prefer AI vs humans. Meta-analysis reveals AI appreciation occurs only when AI seems more capable AND personalization is unnecessary; otherwise people show AI aversion 🧪

doi.org/10.1037/bul0...

Hannah Overbye-Thompson - Drift Diffusion Modeling This page is meant to provide a brief, high-level, non-technical overview of drift diffusion modeling so that you can get an intuition of what Drift Diffusion Models do before you delve into more tech...

Want to learn about drift diffusion modeling (DDM) but not sure where to begin? I put together a short, non-technical intro + curated links to help you get started 👇🧪

🔗 www.hannahoverbye.com/home/drift-d...

Thank you Kylie!

Very happy to see that @overbye.bsky.social’s fantastic work on detecting bias in human-in-the-loop algorithms was awarded a top paper in @icacsab.bsky.social this year. Incredibly interesting, rigorous, and timely research! #ica25

Thank you! Definitely couldn't have done this work without you and your patience in teaching me DDM

Great job @b-wheeler.bsky.social 🥳

Everyone go see Erick present our work on algorithmic bias and risk. He is fantastic! #ICA25

Important Notice!! 😳

Due to @overbye.bsky.social receiving a Top Paper Award from the Communication Science and Biology (CSAB) Interest Group at #ICA25, I’ll now be presenting on behalf of her and our wonderful mixed-methods team: Ceciley Zhang and @laurentwang.bsky.social. Drop by and say hi! 👋🏽