2.3k citations · 2.5k across the 20 of their papers we have counts for
12 papers · 1 filter
Mapping the Podcast Ecosystem with the Structured Podcast Research Corpus
Benjamin Litterer, David Jurgens, Dallas Card
Podcasts provide highly diverse content to a massive listener base through a unique on-demand modality. However, limited data has prevented large-scale computational analysis of th…
Framing Social Movements on Social Media: Unpacking Diagnostic, Prognostic, and Motivational Strategies
Julia Mendelsohn, Maya Vijan, Dallas Card +1
Social media enables activists to directly communicate with the public and provides a space for movement leaders, participants, bystanders, and opponents to collectively construct…
When it Rains, it Pours: Modeling Media Storms and the News Ecosystem
Benjamin Litterer, David Jurgens, Dallas Card
Most events in the world receive at most brief coverage by the news media. Occasionally, however, an event will trigger a media storm, with voluminous and widespread coverage lasti…
Substitution-based Semantic Change Detection using Contextual Embeddings
Dallas Card
Measuring semantic change has thus far remained a task where methods using contextual embeddings have struggled to improve upon simpler techniques relying only on static word vecto…
Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words
Kaitlyn Zhou, Kawin Ethayarajh, Dallas Card +1
Cosine similarity of contextual embeddings is used in many NLP tasks (e.g., QA, IR, MT) and metrics (e.g., BERTScore). Here, we uncover systematic ways in which word similarities e…
Modular Domain Adaptation
Junshen K. Chen, Dallas Card, Dan Jurafsky
Off-the-shelf models are widely used by computational social science researchers to measure properties of text, such as sentiment. However, without access to source data it is diff…
Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection
Suchin Gururangan, Dallas Card, Sarah K. Dreier +5
Language models increasingly rely on massive web dumps for diverse text data. However, these sources are rife with undesirable content. As such, resources like Wikipedia, books, an…
Expected Validation Performance and Estimation of a Random Variable's Maximum
Jesse Dodge, Suchin Gururangan, Dallas Card +2
Research in NLP is often supported by experimental results, and improved reporting of such results can lead to better understanding and more reproducible science. In this paper we…
With Little Power Comes Great Responsibility
Dallas Card, Peter Henderson, Urvashi Khandelwal +3
Despite its importance to experimental design, statistical power (the probability that, given a real effect, an experiment will reject the null hypothesis) has largely been ignored…
Detecting Stance in Media on Global Warming
Yiwei Luo, Dallas Card, Dan Jurafsky
Citing opinions is a powerful yet understudied strategy in argumentation. For example, an environmental activist might say, "Leading scientists agree that global warming is a serio…
Causal Effects of Linguistic Properties
Reid Pryzant, Dallas Card, Dan Jurafsky +2
We consider the problem of using observational data to estimate the causal effects of linguistic properties. For example, does writing a complaint politely lead to a faster respons…
Variational Pretraining for Semi-supervised Text Classification
Suchin Gururangan, Tam Dang, Dallas Card +1
We introduce VAMPIRE, a lightweight pretraining framework for effective text classification when data and computing resources are limited. We pretrain a unigram document model as a…