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Patrick Wu

@patrickwu.bsky.social

Assistant Professor of Computer Science at American University | Computational Politics, NLP, ML/AI | patrickywu.com

9 Posts248 Follower 150 Folgt

Alexander Hoyle @alexanderhoyle.bsky.social · 9mo ago

LLMs are often used for text annotation, especially in social science. In some cases, this involves placing text items on a scale: eg, 1 for liberal and 9 for conservative There are a few ways to accomplish this task. Which work best? Our new EMNLP paper has some answers🧵 arxiv.org/pdf/2507.00828

A diagram illustrating pointwise scoring with a large language model (LLM). At the top is a text box containing instructions: 'You will see the text of a political advertisement about a candidate. Rate it on a scale ranging from 1 to 9, where 1 indicates a positive view of the candidate and 9 indicates a negative view of the candidate.' Below this is a green text box containing an example ad text: 'Joe Biden is going to eat your grandchildren for dinner.' An arrow points down from this text to an illustration of a computer with 'LLM' displayed on its monitor. Finally, an arrow points from the computer down to the number '9' in large teal text, representing the LLM's scoring output. This diagram demonstrates how an LLM directly assigns a numerical score to text based on given criteria

Megan Brown @m-dot-brown.bsky.social · last yr.

Can large language models (LLMs) fairly annotate data on contentious topics? Our new paper dives into this question—looking at whether LLM-generated labels reflect diverse viewpoints or skew toward majority perspectives. The results are surprisingly nuanced. 🧵

Julia Mendelsohn @jmendelsohn2.bsky.social · last yr.

📣 FUN UPDATE: We're extending the deadline by 3 days!! Submit to the NLP4Democracy workshop by June 22!

Julia Mendelsohn@jmendelsohn2.bsky.social · last yr.

📣 Super excited to organize the first workshop on ✨NLP for Democracy✨ at COLM @colmweb.org!! Check out our website: sites.google.com/andrew.cmu.e... Call for submissions (extended abstracts) due June 19, 11:59pm AoE #COLM2025 #LLMs #NLP #NLProc #ComputationalSocialScience

Hannah Waight @hwaight.bsky.social · last yr.

I am thrilled to share a new article in Sociological Methods & Research, “Quantifying Narrative Similarity Across Languages”. My co-first author Sol Messing and our collaborators developed a new approach to measuring “narrative similarity” between texts: journals.sagepub.com/doi/10.1177/...

Quantifying Narrative Similarity Across Languages - Hannah Waight, Solomon Messing, Anton Shirikov, Margaret E. Roberts, Jonathan Nagler, Jason Greenfield, Megan A. Brown, Kevin Aslett, Joshua A. Tuck...

How can one understand the spread of ideas across text data? This is a key measurement problem in sociological inquiry, from the study of how interest groups sh...

journals.sagepub.com

Julia Mendelsohn @jmendelsohn2.bsky.social · last yr.

NLP 4 Democracy - COLM 2025

sites.google.com

Chris Hayes @chrislhayes.bsky.social · last yr.

Unidentified men grabbing someone off the street and putting her in a car because she wrote an op-Ed. This as flatly authoritarian as anything we’ve seen in this country in a very long time.

Matt Novak@paleofuture.bsky.social · last yr.

Video of the international student at Tufts being arrested by "federal authorities" in Massachusetts has been released and it's terrifying. They're not even uniformed officers. Just secret police thugs in hoodies and masks. From WCVB: youtu.be/PuFIs7OkzYY

NYU's Center for Social Media, AI, and Politics @csmapnyu.org · last yr.

It's well known that politicians take more extreme positions during primaries. In @electoralstudies.bsky.social, we find this shift is much more likely when incumbents in safe seats face a well-funded primary challenger. 🧵👇 authors.elsevier.com/a/1kn5KxRaZn...

Brendan Nyhan @brendannyhan.bsky.social · last yr.

Re-upping this again as more people read about the Khalil case. More information to come, but nothing in WP and NYT so far contradicts original reporting. Again, it DOES NOT MATTER what you think about him or his cause. Either government is bound by the law for all of us or we're all at their mercy.

Brendan Nyhan@brendannyhan.bsky.social · last yr.

Reminder: When a person or institution you hate is targeted for illiberal persecution by an aspiring authoritarian, you have to defend them EVEN IF you don't like them. It doesn't matter if you don't like campus protestors or Columbia or the law firms. We must defend them or we're all at risk next.

Max Kozlov @maxkozlov.bsky.social · last yr.

NEW: The NIH has begun terminating grants for active projects studying gender identity, DEI, environmental justice, climate change, among other topics. At least 16 termination letters have already been sent — and hundreds more are coming, people inside NIH tell me. www.nature.com/articles/d41...

Exclusive: NIH to terminate hundreds of active research grants

Studies that touch on LGBT+ health, gender identity and DEI in the biomedical workforce could be terminated, according to documents obtained by Nature.

nature.com

Patrick Wu @patrickwu.bsky.social · last yr.

@adambonica.bsky.social showed ideology predicts which agencies experience DOGE layoffs. But what other factors could be driving this? Using a generative LLM-derived measure, I find agencies perceived as knowledge institutions are more likely to experience layoffs, even controlling for ideology. 🧵

Scatterplot showing various U.S. government agencies plotted with the total staff (on a log scale) on y-axis versus likelihood of being perceived as a knowledge institution on the x-axis. Red dots indicate agencies that have experienced DOGE layoffs, while gray dots indicate agencies without layoffs. Agencies like NIH, NSF, CDC, and NOAA appear on the right side (more likely to be perceived as knowledge institutions), while agencies like ICE, DEA, and Secret Service appear on the left side (less likely to be perceived as knowledge institutions).