Analyzing the Framing of 2020 Presidential Candidates in the News

Audrey Acken, Dorottya Demszky


Abstract
In this study, we apply NLP methods to learn about the framing of the 2020 Democratic Presidential candidates in news media. We use both a lexicon-based approach and word embeddings to analyze how candidates are discussed in news sources with different political leanings. Our results show significant differences in the framing of candidates across the news sources along several dimensions, such as sentiment and agency, paving the way for a deeper investigation.
Anthology ID:
2020.winlp-1.32
Volume:
Proceedings of the Fourth Widening Natural Language Processing Workshop
Month:
July
Year:
2020
Address:
Seattle, USA
Editors:
Rossana Cunha, Samira Shaikh, Erika Varis, Ryan Georgi, Alicia Tsai, Antonios Anastasopoulos, Khyathi Raghavi Chandu
Venue:
WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
123
Language:
URL:
https://aclanthology.org/2020.winlp-1.32
DOI:
10.18653/v1/2020.winlp-1.32
Bibkey:
Cite (ACL):
Audrey Acken and Dorottya Demszky. 2020. Analyzing the Framing of 2020 Presidential Candidates in the News. In Proceedings of the Fourth Widening Natural Language Processing Workshop, page 123, Seattle, USA. Association for Computational Linguistics.
Cite (Informal):
Analyzing the Framing of 2020 Presidential Candidates in the News (Acken & Demszky, WiNLP 2020)
Copy Citation:
Video:
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