Zobrazeno 1 - 10
of 31
pro vyhledávání: '"Beeferman, Doug"'
Understanding and making use of audience feedback is important but difficult for journalists, who now face an impractically large volume of audience comments online. We introduce AudienceView, an online tool to help journalists categorize and interpr
Externí odkaz:
http://arxiv.org/abs/2407.12613
Words often carry different meanings for people from diverse backgrounds. Today's era of social polarization demands that we choose words carefully to prevent miscommunication, especially in political communication and journalism. To address this iss
Externí odkaz:
http://arxiv.org/abs/2407.09661
Autor:
Beeferman, Doug, Gillani, Nabeel
Analyzing open-ended survey responses is a crucial yet challenging task for social scientists, non-profit organizations, and educational institutions, as they often face the trade-off between obtaining rich data and the burden of reading and coding t
Externí odkaz:
http://arxiv.org/abs/2306.15112
Autor:
Gillani, Nabeel, Beeferman, Doug, Overney, Cassandra, Vega-Pourheydarian, Christine, Roy, Deb
Educational data scientists often conduct research with the hopes of translating findings into lasting change through policy, civil society, or other channels. However, the bridge from research to practice can be fraught with sociopolitical frictions
Externí odkaz:
http://arxiv.org/abs/2304.08967
Autor:
Gillani, Nabeel, Beeferman, Doug, Vega-Pourheydarian, Christine, Overney, Cassandra, Van Hentenryck, Pascal, Roy, Deb
Most US school districts draw "attendance boundaries" to define catchment areas that assign students to schools near their homes, often recapitulating neighborhood demographic segregation in schools. Focusing on elementary schools, we ask: how much m
Externí odkaz:
http://arxiv.org/abs/2303.07603
As political attitudes have diverged ideologically in the United States, political speech has diverged lingusitically. The ever-widening polarization between the US political parties is accelerated by an erosion of mutual understanding between them.
Externí odkaz:
http://arxiv.org/abs/2209.07065
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 Recognition (NER) and syntactic parsing require highly domain-matched tr
Externí odkaz:
http://arxiv.org/abs/2201.07281
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 systems aim to cluster a corpus of news articles by event, and in that conte
Externí odkaz:
http://arxiv.org/abs/2112.06166
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 several media outlets over the course of more than three years (566K tweets
Externí odkaz:
http://arxiv.org/abs/2111.02646
Autor:
Beeferman, Doug, Jiang, Hang
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 models to practical applications such as search engines and discovery
Externí odkaz:
http://arxiv.org/abs/2110.07337