Search Results for author: Dorottya Demszky

Found 8 papers, 4 papers with code

Measuring Conversational Uptake: A Case Study on Student-Teacher Interactions

1 code implementation ACL 2021 Dorottya Demszky, Jing Liu, Zid Mancenido, Julie Cohen, Heather Hill, Dan Jurafsky, Tatsunori Hashimoto

In conversation, uptake happens when a speaker builds on the contribution of their interlocutor by, for example, acknowledging, repeating or reformulating what they have said.

Question Answering

Learning to Recognize Dialect Features

no code implementations NAACL 2021 Dorottya Demszky, Devyani Sharma, Jonathan H. Clark, Vinodkumar Prabhakaran, Jacob Eisenstein

Evaluation on a test set of 22 dialect features of Indian English demonstrates that these models learn to recognize many features with high accuracy, and that a few minimal pairs can be as effective for training as thousands of labeled examples.

Analyzing the Framing of 2020 Presidential Candidates in the News

no code implementations WS 2020 Audrey Acken, Dorottya Demszky

In this study, we apply NLP methods to learn about the framing of the 2020 Democratic Presidential candidates in news media.

Word Embeddings

The Role of Verb Semantics in Hungarian Verb-Object Order

no code implementations16 Jun 2020 Dorottya Demszky, László Kálmán, Dan Jurafsky, Beth Levin

We test the effect of lexical semantics on the ordering of verbs and their objects by grouping verbs into 11 semantic classes.

P\'art\'elet: A Hungarian Corpus of Propaganda Texts from the Hungarian Socialist Era

no code implementations LREC 2020 Zolt{\'a}n Kmetty, Veronika Vincze, Dorottya Demszky, Orsolya Ring, Bal{\'a}zs Nagy, Martina Katalin Szab{\'o}

P{\'a}rt{\'e}let was the official journal of the governing party during the Hungarian socialism from 1956 to 1989, hence it represents the direct political agitation and propaganda of the dictatorial system in question.

GoEmotions: A Dataset of Fine-Grained Emotions

7 code implementations ACL 2020 Dorottya Demszky, Dana Movshovitz-Attias, Jeongwoo Ko, Alan Cowen, Gaurav Nemade, Sujith Ravi

Understanding emotion expressed in language has a wide range of applications, from building empathetic chatbots to detecting harmful online behavior.

Emotion Classification Transfer Learning

Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootings

1 code implementation NAACL 2019 Dorottya Demszky, Nikhil Garg, Rob Voigt, James Zou, Matthew Gentzkow, Jesse Shapiro, Dan Jurafsky

We provide an NLP framework to uncover four linguistic dimensions of political polarization in social media: topic choice, framing, affect and illocutionary force.

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