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Lisa Argyle

@lpargyle.bsky.social

Associate Professor of Political Science at Purdue. Study: Political Conversation, Polarization, Computational Social Science, LLMs

16 Posts389 Follower215 Folgt
Lisa Argyle@lpargyle.bsky.social · 5mo ago

Pol comm scholars! Who has had a big impact on your career? Why don't you thank them by nominating them for this great new award? I'm on the committee, so send it my way!

APSA & ICA Political Communication Divisions@polcomm.bsky.social · 5mo ago

The deadline for nominations for the APSA PolComm Award, the "Excellence in Political Communication Mentorship Award," has been extended. Nominations are open until April 1. More details at: politicalcommunication.org/awards/

Emily Sydnor@esydnor.bsky.social · 6mo ago

I'm chairing the brand new "Excellence in Mentoring in Political Communication" award, with @lpargyle.bsky.social, Michael Chan and Dan Myers--please nominate scholars who you believe have supported the next generation of scholars through advising and other forms of mentorship!

APSA & ICA Political Communication Divisions@polcomm.bsky.social · 6mo ago

The APSA Political Communication section is accepting nominations for its annual awards. Please send nominations directly to the chair of each committee. 🔎 More details on awards, committee, and eligibility criteria: politicalcommunication.org/awards/

Lisa Argyle@lpargyle.bsky.social · 8mo ago

Looking for a tl;dr for these two excellent papers? I've got you covered: www.science.org/doi/10.1126/...

Political persuasion by artificial intelligence

Large-scale studies of persuasive artificial intelligence reveal an extensive threat of misinformation

science.org

David Rand@dgrand.bsky.social · 8mo ago

🚨 New in Nature+Science!🚨 AI chatbots can shift voter attitudes on candidates & policies, often by 10+pp 🔹Exps in US Canada Poland & UK 🔹More “facts”→more persuasion (not psych tricks) 🔹Increasing persuasiveness reduces "fact" accuracy 🔹Right-leaning bots=more inaccurate

Nature Computational Science@natcomputsci.nature.com · 11mo ago

📢 @lpargyle.bsky.social, @ethanbusby.bsky.social and colleagues discuss in a Perspective the challenges and opportunities related to scientific inference with LLMs in the political and social sciences. www.nature.com/articles/s43... #cssky #PoliSci 🔓https://rdcu.be/eGwK9

Arti-‘fickle’ intelligence: using LLMs as a tool for inference in the political and social sciences - Nature Computational Science

Large language models are increasingly important in social science research. The authors provide guidance on how best to validate and use these models as rigorous tools to further scientific inference...

nature.com

Lisa Argyle@lpargyle.bsky.social · last yr.

Excited to see this excellent collection of papers come out! Many thanks to @thomasdavidson.bsky.social and Daniel Karell

Thomas Davidson@thomasdavidson.bsky.social · last yr.

I’m delighted to share that the August 2025 special issue of Sociological Methods & Research on Generative AI is out now. Along with my co-editor, Daniel Karell, we put together this issue to build on the conference we organized last year. Here's a thread on each of the ten papers:

A screenshot of the Sociological Methods & Research website showing the special issue title
Jon Green@jongreen.bsky.social · 2y ago

Ok, thread time. Closed-ended survey responses are efficient and easy to analyze, but limit what respondents can say. Open-ended responses are useful for letting respondents answer with more depth in their own words (as opposed to yours).

Jon Green@jongreen.bsky.social · 2y ago

Online/open access in @polanalysis.bsky.social w/ @willrhobbs.bsky.social: a theory and method for inferring attitudes in open-ended survey responses www.cambridge.org/core/journal...

Abstract: Past work on closed-ended survey responses demonstrates that inferring stable political attitudes requires separating signal from noise in “top of the head” answers to researchers’ questions. We outline a corresponding theory of the open-ended response, in which respondents make narrow, stand-in statements to convey more abstract, general attitudes. We then present a method designed to infer those attitudes. Our approach leverages co-variation with words used relatively frequently across respondents to infer what else they could have said without substantively changing what they meant—linking narrow themes to each other through associations with contextually prevalent words. This reflects the intuition that a respondent may use different specific statements at different points in time to convey similar meaning. We validate this approach using panel data in which respondents answer the same open-ended questions (concerning healthcare policy, most important problems, and evaluations of political parties) at multiple points in time, showing that our method’s output consistently exhibits higher within-subject correlations than hand-coding of narrow response categories, topic modeling, and large language model output. Finally, we show how large language models can be used to complement—but not, at present, substitute—our “implied word” method.
Lisa Argyle@lpargyle.bsky.social · 2y ago

Computational Political Scientists: @EthanBusby and I are organizing a CWC at @spsanews on Generative Language Models. Apply by August 16; Conference in Puerto Rico Jan 8 - 11. Please apply and circulate widely! forms.gle/vJoU2ZaMp773... polisky

SPSA 2025 CWC: Generative Language Models in Political Science Research

Apply here for a Conference-Within-a-Conference to be held at the 2025 SPSA Annual Meeting, January 8 - 11 Caribe Hilton, San Juan Puerto Rico. CWC Scope: The topic of the CWC is Generative Language...

forms.gle

Luke Thorburn@lukethorburn.com · 3y ago

Recent study by Lisa Argyle, Chris Bail et al. showing that using an LLM to suggest rephrasings in conversations about divisive topics can improve perceived conversation quality and feelings of democratic reciprocity — without any apparent manipulation of political views. doi.org/10.1073/pnas...