100 citations · 136 across the 7 of their papers we have counts for
8 papers
CommunityLM: Probing Partisan Worldviews from Language Models
Hang Jiang, Doug Beeferman, Brandon Roy +1
As political attitudes have diverged ideologically in the United States, political speech has diverged lingusitically. The ever-widening polarization between the US political parti…
Annotating the Tweebank Corpus on Named Entity Recognition and Building NLP Models for Social Media Analysis
Hang Jiang, Yining Hua, Doug Beeferman +1
Social media data such as Twitter messages ("tweets") pose a particular challenge to NLP systems because of their short, noisy, and colloquial nature. Tasks such as Named Entity Re…
Topic Detection and Tracking with Time-Aware Document Embeddings
Hang Jiang, Doug Beeferman, Weiquan Mao +1
The time at which a message is communicated is a vital piece of metadata in many real-world natural language processing tasks such as Topic Detection and Tracking (TDT). TDT system…
Engaging Politically Diverse Audiences on Social Media
Martin Saveski, Doug Beeferman, David McClure +1
We study how political polarization is reflected in the social media posts used by media outlets to promote their content online. In particular, we track the Twitter posts of sever…
Topic-time Heatmaps for Human-in-the-loop Topic Detection and Tracking
Doug Beeferman, Hang Jiang
The essential task of Topic Detection and Tracking (TDT) is to organize a collection of news media into clusters of stories that pertain to the same real-world event. To apply TDT…
RadioTalk: a large-scale corpus of talk radio transcripts
Doug Beeferman, William Brannon, Deb Roy
We introduce RadioTalk, a corpus of speech recognition transcripts sampled from talk radio broadcasts in the United States between October of 2018 and March of 2019. The corpus is…
A Model of Lexical Attraction and Repulsion
Doug Beeferman, Adam Berger, John Lafferty
This paper introduces new methods based on exponential families for modeling the correlations between words in text and speech. While previous work assumed the effects of word co-o…
Text Segmentation Using Exponential Models
Doug Beeferman, Adam Berger, John Lafferty
This paper introduces a new statistical approach to partitioning text automatically into coherent segments. Our approach enlists both short-range and long-range language models to…