Lindsay Hahn

@lindsayhahn.bsky.social

assoc prof, u at buffalo • media psychology, morality • mediamoralitylab.org

5/n We engage this debate by taking a slightly different approach Rather than ask if summary statistics detect bots after the fact, we ask: what does it actually take to build a bot that can do a real task, live, through a browser, under real timing constraints?

Hey y'all! Very pleased to announce that we'll be hosting Communication Science Futures again in East Lansing later this year. The conference in 2024 was a blast, and we're looking forward to running it back! Keynote speaker: James Pennebaker Submission deadline: June 5th. → commscifutures.com

Home | Communication Science Futures

Communication Science Futures is a conference aimed at addressing pressing issues and opportunities in the interdisciplinary, social...

commscifutures.com

How do we deal with rich, multilevel, and multimodal data? In a new preprint, @rachaelkee.bsky.social and I sketch an answer! For all the details, and the preprint link, see Rachael’s thread. Be sure to give her a follow, especially if you’re interested in neuroscience, sleep, and media!

Three-panel infographic illustrating Marr’s Levels of analysis in a study of repeated exposure to crime media.
(a) At the top left, a diagram labeled “Marr’s Levels” shows three stacked boxes: 1. Computation (why / problem) in orange, 2. Algorithm (what / rules) in coral, and 3. Implementation (how / physical) in dark red.
(b) At the top right, an illustration of a person looking at a smartphone surrounded by social media icons, a warning symbol, and a clock, labeled “Repeated exposure to crime media.”
(c) The bottom row maps each level to research methods: Computation shows a person with checklist icons and the text “EMA/ESM surveys, in-app surveys, pop-up questionnaires.” Algorithm shows a smartphone social media interface with the text “Digital trace data, smartphone usage logs, screen time APIs.” Implementation shows a person interacting with a smartwatch and the text “Wearable biometric sensors (e.g., smartwatches, Oura ring), consumer-grade EEG (e.g., MUSE headbands), eyetracking devices (e.g., Gazepoint GP3).”
Rachael Kee@rachaelkee.bsky.social · 5mo ago

🚨 New Preprint Alert 🚨 Communication science has no shortage of data. But what do we do with all of it? Experience sampling, sensors, digital trace, location aware observations are growing in popularity and scale.

🚨 New Preprint Alert 🚨 Communication science has no shortage of data. But what do we do with all of it? Experience sampling, sensors, digital trace, location aware observations are growing in popularity and scale.

I’ll have more to say about this paper in a bit, but very excited about it. Helps to explain why punishment doesn’t work to improve cooperation, why people still punish anyway, and what it implies about the evolution of cooperation and criminal justice policy www.pnas.org/doi/10.1073/...

Profitable third-party punishment destabilizes cooperation | PNAS

Third-party punishment is theorized by some scholars to be essential to the evolution of large-scale cooperation, but empirically, it often fails t...

pnas.org

I’m thrilled to announce that I’ve joined Boston University as an Assistant Professor in Media Psychology and AI. I’ll be part of the Department of Mass Comm, Advertising, & PR as well as the Division of Emerging Media Studies. I’m excited to work with this incredible group of scholars.

@lindsayhahn.bsky.social advocates for translational science principles to bridge the gap between CAM research, public understanding & policy on media’s effects on children by, for instance, prioritizing research addressing caregivers’ and educators’ needs (6/8) www.tandfonline.com/doi/full/10....

A call for the adoption of translational science principles in children’s media effects research

Published in Journal of Children and Media (Ahead of Print, 2025)

tandfonline.com