no code implementations • NAACL (SocialNLP) 2021 • Savannah Larimore, Ian Kennedy, Breon Haskett, Alina Arseniev-Koehler
Using annotations of 5188 tweets from 291 annotators, we investigate how annotator perceptions of racism in tweets vary by annotator racial identity and two text features of the tweets: relevant keywords and latent topics identified through structural topic modeling.
no code implementations • 22 Jul 2021 • Alina Arseniev-Koehler
Measuring meaning is a central problem in cultural sociology and word embeddings may offer powerful new tools to do so.
1 code implementation • 28 Jun 2021 • Alina Arseniev-Koehler, Susan D. Cochran, Vickie M. Mays, Kai-Wei Chang, Jacob Gates Foster
Our method offers a flexible and broadly applicable approach to model topics in text data.
no code implementations • NAACL 2021 • Ankith Uppunda, Susan D. Cochran, Jacob G. Foster, Alina Arseniev-Koehler, Vickie M. Mays, Kai-Wei Chang
Coreference resolution is an important component in analyzing narrative text from administrative data (e. g., clinical or police sources).
1 code implementation • 24 Mar 2020 • Alina Arseniev-Koehler, Jacob G. Foster
Such schemata may be subtly but pervasively activated in public culture; thus, language can chronically reproduce biases.
Cultural Vocal Bursts Intensity Prediction Language Modelling +2
no code implementations • WS 2018 • Alina Arseniev-Koehler, Sharon Mozgai, Stefan Scherer
Computational models to detect mental illnesses from text and speech could enhance our understanding of mental health while offering opportunities for early detection and intervention.