Very delighted to announce the next step in my career! After my postdoc at ETH, I will begin a joint appointment at TU Wien and the Complexity Science Hub Vienna as an Assistant Professor in NLP. I'm so grateful to all who helped me along the way And yes, I’m hiring! Details on PhD positions below

Computational approaches to media narrative analysis either miss nuanced storytelling patterns through coarse-grained analysis, or require domain-specific taxonomies that limit scalability. We show joint event and character modeling can address this gap. Details in our #ACL2026 (Main) paper. 🧵1/10

This paper is getting a lot of (deserved) attention; I think this paper serves as a nice complement arxiv.org/abs/2602.18710

What’s the best way to analyze online discourse on any given topic? Is there a right way to use NLP tools to sift through massive datasets? To find out, we tested several tools across different collaboration settings and report findings in an #ACL2026 (Main) paper: arxiv.org/abs/2408.09030 🧵1/7

This article has been making the rounds, but someone else pointed out that the "evidence" is based on LLM-simulated users. I have extremely low faith in the validity of these results, especially given the established stickiness of political beliefs and the known issues with in-silica simulation

I wrote a blog post on my experience using AI for slide generation Basic idea: write your lecture notes first, then prompt the LLM to produce corresponding slides in reveal.js (h/t @chenhaotan.bsky.social). I'm picky about my slides but was happy with the results! alexanderhoyle.com/posts/ai-sli...

Happy to be at #EMNLP2025! Please say hello and come see our lovely work

[corrected link] LLMs are often used for text annotation 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 handle this task. Which work best? Our new EMNLP paper has some answers🧵 arxiv.org/abs/2509.03116

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

Computer Science is no longer just about building systems or proving theorems--it's about observation and experiments. In my latest blog post, I argue it’s time we had our own "Econometrics," a discipline devoted to empirical rigor. doomscrollingbabel.manoel.xyz/p/the-missin...

Accepted to EMNLP (and more to come 👀)! The camera ready version is now online---very happy with how this turned out arxiv.org/abs/2507.01234

this looks terrific, very excited to read

I am delighted to share our new #PNAS paper, with @grvkamath.bsky.social @msonderegger.bsky.social and @sivareddyg.bsky.social, on whether age matters for the adoption of new meanings. That is, as words change meaning, does the rate of adoption vary across generations? www.pnas.org/doi/epdf/10....

At #ACL2025 this week! Please reach out if you want to chat :) We have two lovely posters: Tues Session 2, 10:30-11:50 — Large Language Models Struggle to Describe the Haystack without Human Help Wed Session 4 11:00-12:30 — ProxAnn: Use-Oriented Evaluations of Topic Models and Document Clustering

🗣️ Excited to share our new #ACL2025 Findings paper: “Just Put a Human in the Loop? Investigating LLM-Assisted Annotation for Subjective Tasks” with Jad Kabbara and Deb Roy. Arxiv: arxiv.org/abs/2507.15821 Read about our findings ⤵️

The precursor to this paper "The Incoherence of Coherence" had our most-watched paper video ever, so I thought we had to surpass it somehow ... so we decided to do a song parody (of Roxanne, obviously): youtu.be/87OBxEM8a9E

New preprint! Have you ever tried to cluster text embeddings from different sources, but the clusters just reproduce the sources? Or attempted to retrieve similar documents across multiple languages, and even multilingual embeddings return items in the same language? Turns out there's an easy fix🧵

Evaluating topic models (and document clustering methods) is hard. In fact, since our paper critiquing standard evaluation practices four years ago, there hasn't been a good replacement metric That ends today (we hope)! Our new ACL paper introduces an LLM-based evaluation protocol 🧵

Michael Roth's recent outspokenness has made me proud to be a Wes alum. A decade of NYT op-ed handwringing about "free speech" on campuses has only provided ammunition for bad faith attacks on academia (Perhaps I should be better at responding to those fundraising emails)

I for one am grateful for the opportunity to meditate on the meaning of “scientific artifact” at 2:15am

They added multi-file search!

Heartbreaking and evil. International students have always been treated like an indentured underclass, but we’ve moved from byzantine indifference to deliberate terrorizing. Unforgivable Are there mutual aid networks for international students? What can we as citizens do here?

this holiday season I am thankful that, rather than fixing the literally decade-old problem of multi-file search, Overleaf instead implemented the world's worst writing assistance tool

BERTopic users: how do you retrieve the documents most associated with a given topic? I can see some possible options from the documentation, but I'm most interested in standard practice (NB: please don't take this question as a tacit endorsement of BERTopic, I'm just trying to evaluate it fairly)

Maria has been a consistent source of excellent insight, advice, and research since I’ve known her—you should apply! (And now the bluesky is taking off you will be connected to NLP’s #1 influencer ! )

Once again thinking about this description of a George Wallace campaign rally (from Gary Wills’ “Nixon Agonistes”)

if a computer told you how fucking stupid this is would you believe it twitter.com/emollick/sta...

What is in the water in Amsterdam?? For my dissertation I've been reading these excellent critical papers on measurement and validation and so many authors have a connection to UvA pubmed.ncbi.nlm.nih.gov/15482073/ www.tandfonline.com/doi/epdf/10.... www.tandfonline.com/doi/full/10....

The #DataSittersClub is back with an all-new book on topic modeling! If the LDA buffet explainer didn't do it for you, give this one a try: thanks to Xanda Schofield and her student Sathvika Anand, I now feel like I actually understand how it works. datasittersclub.github.io/site/dsc20.h...

Dominik @dominsta.bsky.social talks about how to evaluate topic models, particularly with LLMs. 📄🧾📑🗞️📰📜 Joint work with Alexander @alexanderhoyle.bsky.social, Mrinmaya Sachan, and Elliott @elliottash.bsky.social. www.youtube.com/watch?v=qIDj...

Honored my paper was accepted to Findings of #EMNLP2023! Many psycholinguistics studies use LLMs to estimate the probability of words in context. But LLMs process statistically derived subword tokens, while human processing doesn't. Does this matter? (w/Philip Resnik) 🧵 arxiv.org/abs/2310.17774