Andy Halterman

NLP, event extraction, and political violence. Assistant professor of political science at MSU. PhD from MIT. Mastodon: @[email protected]

[Political Analysis @polanalysis]

Currently in FirstView: “Synthetically generated text for supervised text analysis.” @ahalterman proposes a method for using LLMs to generate synthetic training data for training smaller, traditional supervised text models.

[Andy Halterman @ahalterman]

@arthur_spirling @cbarrie @brendan642 Unfortunately pretty much none of them do, because of licensing/copyright issues. The best I've seen is a news source + headlines, which you can (sometimes, painfully) use to get the original text, but it's not easy.

[brendan o'connor @brendan642]

Reminder - for the terrific interdisciplinary Text as Data conference, abstract submissions coming up - due Aug 4!

https://t.co/BjegNt4qpv

It's a great, small, non-archival conference to discuss emerging work with folks across social sciences, humanities, and computer science.

[Andy Halterman @ahalterman]

Or if you're interesting in forecasting civil war as a latent variable, you can come talk to me about that too.

[Andy Halterman @ahalterman]

MSU political science is hiring in methods! I'm at PolMeth today if you want chat about it. https://t.co/VLhaVM1Lkf

[Andy Halterman @ahalterman]

Blog post: https://t.co/CEartyQPu6
Live demo: https://t.co/2PW2x1dtxP
Paper: https://t.co/V7vI8buzpp

[Andy Halterman @ahalterman]

How can we categorize political actors extracted from text without or dictionaries or lots of hand labeling? We can use a "soft dictionary" approach with a small set of hand-written patterns and a transformer model.

[Arthur Spirling @arthur_spirling]

OK, here it is: a line in the sand (in @Nature). I am very wary about scientists---including political scientists---embracing/pushing proprietary LLMs. Let's try an open science approach. Hope this take is a useful one.
https://t.co/jvb4tK8lE2

[Andy Halterman @ahalterman]

Big epiphanies today in the grad causal inference class reviewing all the methods we've covered so far.

[Andy Halterman @ahalterman]

No ChatGPT here (yet), only the finest, handcrafted, artisanal features and good old RoBERTa.

[Andy Halterman @ahalterman]

I've (finally) released an update to my text geoparsing library. Mordecai 3 lets you pass in a document, and returns the place names from the text and their geographic coordinates. It's built on #spacy and Geonames and uses a new neural similarity model.

[Andy Halterman @ahalterman]

Mordecai 3 is open source, runs offline, and is available via pip or on GitHub: https://t.co/RVPnCux6vT. Check out the paper for more details and performance comparisons with other geoparsers: https://t.co/zLhn2IjUfj

[cs.CL Papers @arxiv_cs_cl]

https://t.co/dqZ3kuhaIh Creating Custom Event Data Without Dictionaries: A Bag-of-Tricks. (arXiv:2304.01331v1 [https://t.co/HW5RVw4UkE]) #NLProc

[Andy Halterman @ahalterman]

@a_strezh It’s a lie!

[Andy Halterman @ahalterman]

@emollick Not a special issue, but I have a working paper on using synthetically generated text to train supervised classifiers (with poli sci applications). Paper: https://t.co/YWcMpuuh8k Poster: https://t.co/qWIvb3HSIa

[Andy Halterman @ahalterman]

@emollick The main guidance is on how to guide the text generation (when to prompt vs. when to fine tune) and how to handle the output (hand label or zero shot). ChatGPT is definitely moving things toward prompt+zero shot.

[Andy Halterman @ahalterman]

@emollick Not a special issue, but I have a working paper on using synthetically generated text to train supervised classifiers (with poli sci applications). Paper: https://t.co/YWcMpuuh8k Poster: https://t.co/qWIvb3HSIa

[Niklas Stoehr @niklas_stoehr]

@ben_j_radford and @hurrial kicking off the second day of the #CASE Workshop (Extraction of Socio-political Events from Text) @emnlpmeeting. @ahalterman @tiancheng_hu @yaoyao_dai @HristoTanev2 🙌

[MIT SSP @MIT_SSP]

Much of IR is concerned with understanding the behavior of elites. That’s nice from a natural language processing perspective, as elite decision-making tend to get written down.

— SSP alum @ahalterman on natural language processing in IR research.

https://t.co/4saIhRmpiA

[Andy Halterman @ahalterman]

@arnicas Every time I sit down to make a Streamlit demo, I think “this will probably take a couple hours”, and then it takes like 20 minutes. It’s a really nice tool!