Analyzing the Framing of 2020 Presidential Candidates in the News
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Word EmbeddingsSimilar Papers 제목 키워드 기반
Political Framing: US COVID19 Blame Game
Through the use of Twitter, framing has become a prominent presidential campaign tool for politically active users. Framing is used to influence thoughts by evoking a particular perspective on an event. In this paper, we…
Analyzing Framing through the Casts of Characters in the News
FrameFinder: Explorative Multi-Perspective Framing Extraction from News Headlines
Revealing the framing of news articles is an important yet neglected task in information seeking and retrieval. In the present work, we present FrameFinder, an open tool for extracting and analyzing frames in textual dat…
ArticlesRetrievalOn the Challenges of Sentiment Analysis for Dynamic Events
With the proliferation of social media over the last decade, determining people's attitude with respect to a specific topic, document, interaction or events has fueled research interest in natural language processing and…
Emotion RecognitionMarketingSentiment AnalysisTopic Signatures in Political Campaign Speeches
Highlighting the recurrence of topics usage in candidates speeches is a key feature to identify the main ideas of each candidate during a political campaign. In this paper, we present a method combining standard topic mo…