To Protect and To Serve? Analyzing Entity-Centric Framing of Police Violence
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Abstract (arXiv)
Framing has significant but subtle effects on public opinion and policy. We propose an NLP framework to measure entity-centric frames. We use it to understand media coverage on police violence in the United States in a new Police Violence Frames Corpus of 82k news articles spanning 7k police killings. Our work uncovers more than a dozen framing devices and reveals significant differences in the way liberal and conservative news sources frame both the issue of police violence and the entities involved. Conservative sources emphasize when the victim is armed or attacking an officer and are more likely to mention the victim's criminal record. Liberal sources focus more on the underlying systemic injustice, highlighting the victim's race and that they were unarmed. We discover temporary spikes in these injustice frames near high-profile shooting events, and finally, we show protest volume correlates with and precedes media framing decisions.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 20 of its 107 references that are in the map. First posted on arXiv 11 Sep 2021.
Builds on
20 of 107 references.
References · 20
- 2020We Can Detect Your Bias: Predicting the Political Ideology of News Articlescited by 92
- 2018Predicting Factuality of Reporting and Bias of News Media Sourcescited by 71
- 2019Analyzing Polarization in Social Media: Method and Application to Tweets on 21 Mass Shootingscited by 67
- 2016Deep Reinforcement Learning for Mention-Ranking Coreference Modelscited by 63
- 2016Empath: Understanding Topic Signals in Large-Scale Textcited by 51
- 2020Detecting Stance in Media on Global Warmingcited by 48
- 2018Framing and Agenda-setting in Russian News: a Computational Analysis of Intricate Political Strategiescited by 47
- 2020Detecting East Asian Prejudice on Social Mediacited by 40
- 2020Racism is a Virus: Anti-Asian Hate and Counterspeech in Social Media during the COVID-19 Crisiscited by 40
- 2021Modeling Framing in Immigration Discourse on Social Mediacited by 37
- 2020Moral Framing and Ideological Bias of Newscited by 29
- 2020Weakly Supervised Learning of Nuanced Frames for Analyzing Polarization in News Mediacited by 27
8 more
- 2019Multi-Task Ordinal Regression for Jointly Predicting the Trustworthiness and the Leading Political Ideology of News Mediacited by 26
- 2019FAKTA: An Automatic End-to-End Fact Checking Systemcited by 13
- 2019Entity-Centric Contextual Affective Analysiscited by 11
- 2017Identifying civilians killed by police with distantly supervised entity-event extractioncited by 9
- 2019Predicting the Leading Political Ideology of YouTube Channels Using Acoustic, Textual, and Metadata Informationcited by 9
- 2018Who is Killed by Police: Introducing Supervised Attention for Hierarchical LSTMscited by 7
- 2019Contextual Affective Analysis: A Case Study of People Portrayals in Online #MeToo Storiescited by 7
- 2021Mapping Moral Valence of Tweets Following the Killing of George Floydcited by 4
Built on by
Citing papers per year: 2022: 2; 2023: 3; 2024: 1; 2025: 5; 2026: 1.
12 papers.
- 2023Can Large Language Models Transform Computational Social Science?cited by 245
- 2024Measuring Political Bias in Large Language Models: What Is Said and How It Is Saidcited by 89
- 2022Multi-VALUE: A Framework for Cross-Dialectal English NLPcited by 51
- 2023Connecting the Dots in News Analysis: Bridging the Cross-Disciplinary Disparities in Media Bias and Framingcited by 6
- 2025Framing Political Bias in Multilingual LLMs Across Pakistani Languagescited by 5
- 2025Read Between the Lines: A Benchmark for Uncovering Political Bias in Bangla News Articlescited by 5
- 2022Zero-Shot Classification by Logical Reasoning on Natural Language Explanationscited by 4
- 2023"A Tale of Two Movements": Identifying and Comparing Perspectives in #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly Supervised Graph-based Structured Predictioncited by 4
- 2025Uncovering Hidden Violent Tendencies in LLMs: A Demographic Analysis via Behavioral Vignettescited by 1
- 2025Fane at SemEval-2025 Task 10: Zero-Shot Entity Framing with Large Language Modelscited by 0
- 2025Semantic-based Unsupervised Framing Analysis (SUFA): A Novel Approach for Computational Framing Analysiscited by 0
- 2026Quantifying Media Representation Dynamics Across 25 Years of News Reporting on Policing-related Deathscited by 0
- 2026Quantifying Media Representation Dynamics Across 25 Years of News Reporting on Policing-related Deaths5 Jun 2026
- 2025Read Between the Lines: A Benchmark for Uncovering Political Bias in Bangla News Articles4 Oct 2025
- 2025Uncovering Hidden Violent Tendencies in LLMs: A Demographic Analysis via Behavioral Vignettes25 Jun 2025
- 2025Framing Political Bias in Multilingual LLMs Across Pakistani Languages29 May 2025
- 2025Semantic-based Unsupervised Framing Analysis (SUFA): A Novel Approach for Computational Framing Analysis21 May 2025
- 2025Fane at SemEval-2025 Task 10: Zero-Shot Entity Framing with Large Language Models29 Apr 2025
- 2024Measuring Political Bias in Large Language Models: What Is Said and How It Is Said27 Mar 2024
- 2023"A Tale of Two Movements": Identifying and Comparing Perspectives in #BlackLivesMatter and #BlueLivesMatter Movements-related Tweets using Weakly Supervised Graph-based Structured Prediction11 Oct 2023
- 2023Connecting the Dots in News Analysis: Bridging the Cross-Disciplinary Disparities in Media Bias and Framing14 Sep 2023
- 2023Can Large Language Models Transform Computational Social Science?12 Apr 2023
- 2022Multi-VALUE: A Framework for Cross-Dialectal English NLP15 Dec 2022
- 2022Zero-Shot Classification by Logical Reasoning on Natural Language Explanations7 Nov 2022