15 citations · 19 across the 4 of their papers we have counts for
6 papers · 1 filter
Tell, Don't Show: Leveraging Language Models' Abstractive Retellings to Model Literary Themes
Li Lucy, Camilla Griffiths, Sarah Levine +3
Conventional bag-of-words approaches for topic modeling, like latent Dirichlet allocation (LDA), struggle with literary text. Literature challenges lexical methods because narrativ…
On Classification with Large Language Models in Cultural Analytics
David Bamman, Kent K. Chang, Li Lucy +1
In this work, we survey the way in which classification is used as a sensemaking practice in cultural analytics, and assess where large language models can fit into this landscape.…
Discovering Differences in the Representation of People using Contextualized Semantic Axes
Li Lucy, Divya Tadimeti, David Bamman
A common paradigm for identifying semantic differences across social and temporal contexts is the use of static word embeddings and their distances. In particular, past work has co…
Characterizing English Variation across Social Media Communities with BERT
Li Lucy, David Bamman
Much previous work characterizing language variation across Internet social groups has focused on the types of words used by these groups. We extend this type of study by employing…
Using Sentiment Induction to Understand Variation in Gendered Online Communities
Li Lucy, Julia Mendelsohn
We analyze gendered communities defined in three different ways: text, users, and sentiment. Differences across these representations reveal facets of communities' distinctive iden…
Are distributional representations ready for the real world? Evaluating word vectors for grounded perceptual meaning
Li Lucy, Jon Gauthier
Distributional word representation methods exploit word co-occurrences to build compact vector encodings of words. While these representations enjoy widespread use in modern natura…