Thank you so much, Hannah!!
Thank you!!! Would be happy to hear your thoughts! ☺️
Thank you, Richard!
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!
15/15
If communication processes are dynamic, our science needs to be dynamic too.
Preprint: doi.org/10.33767/osf...
14/15
The goal is a communication science that is:
• more temporally precise
• more ecologically valid
• better equipped to test the dynamic causal mechanisms underlying human communication.
13/15
Additionally, recent advances in causal modeling also provide the opportunity to test our theories in ways previously unavailable due to statistical constraints.
12/15
Importantly, this agenda is not just aspirational, it’s practical.
The tools needed for high-throughput communication science (e.g., wearables, smartphone logs) are increasingly accessible across labs, subfields, and research settings.
11/15
Our paper provides a roadmap for connecting subjective experience, behavior over time, and biological implementation under one unifying framework.
This approach helps to unite domains that are often studied separately but can be integrated through high-throughput data collection.
10/15
To situate this agenda, we connect high-throughput communication science to multilevel causal explanation, drawing on Marr’s Tri-Level Framework:
• why a process occurs
• what rules govern it
• how it is physically instantiated
9/15
Moreover, these data are collected in context and at meaningful temporal scales.
8/15
High-throughput communication science helps realign our method and theory by integrating data streams at multiple levels, including:
• psychological (e.g., self-reports)
• behavioral (e.g., platform logs)
• biological (e.g., HRV)
7/15
If we want to understand communication as it actually happens, our measurement strategies need to better reflect these time-sensitive and context-dependent processes.
6/15
That mismatch limits the strength of our causal inferences and how we explain causal mechanisms of real-world communication dynamics.
5/15
Many communication theories make claims about processes that unfold over time, across contexts, and across levels of analysis.
But our methods often capture only static snapshots.
4/15
The real challenge isn’t how much data we have, it’s that the methods we use to collect it and the theories we use to justify it are often misaligned.
3/15
In a new preprint, Richard Huskey @richardhuskey.bsky.social and I introduce high-throughput communication science: a research agenda for leveraging rich, multimodal data streams to understand communication dynamics in context, at scale, and over time.
doi.org/10.33767/osf...
2/15
We keep gathering more and more data at finer and finer timescales, but… so what?
What can be done with it? And how do we integrate it?
🚨 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.
Dear hackers, meet Marvin!! 🐧 Marvin is a South African Penguin who loves eating squid and developing R packages for his friends. Marvin's also here to remind you to register for some #hackica26 fun 🔽
Thank you, Juergen!! 🥳
Feeling so grateful for being able to engage in such an exciting conversation in a room full of superstars! Thankful for my QE Committee, for my advisor, and for finally reaching this milestone! Next steps… even greater things! 🤩
Good news! 🎉
The registration issue has been resolved — everything should now work smoothly.
🔗 Direct link: www.icahdq.org/event/Hackat...
🗓 Registration is open until April 5, 2026
Looking forward to seeing you at the ICA Hackathon 2026 @SU School for Data Science and Computational Thinking! 🚀💡
✨We’re live!
Our updated Hackathon website is online — explore it here for more information: hackingcommsci.org 🎉
You’ll find everything you need to know for the event at the SU School for Data Science and Computational Thinking in Stellenbosch on 3rd–4th of June 2026 🇿🇦
thinking about how there's a true solution to the trolley problem and union workers were the ones to point it out
Very excited about this project introducing an integrative character-based network framework predicting success of novels and films. Idea and analysis credit to @gongxuanjun.bsky.social, with big thanks for including me, @fhopp.bsky.social @mattgrizz.bsky.social and Anna Wolfe. More info here:
Enjoying Stranger Things during the holiday season? Have you thought about why some stories are more successful than others? Our new preprint investigates this question by studying the character networks in the narratives:
osf.io/preprints/ps...
Best MRI demo I’ve ever seen. Accurate. (Sound on).
Sleep and digital health in autism and other neurodevelopmental conditions:
www.nature.com/articles/s41...
Happy new year to all !
With some trepidation, I'm putting this out into the world:
gershmanlab.com/textbook.html
It's a textbook called Computational Foundations of Cognitive Neuroscience, which I wrote for my class.
My hope is that this will be a living document, continuously improved as I get feedback.
