What Makes Gun Violence a (Less) Prominent Issue? A Computational Analysis of Compelling Arguments and Selective Agenda Setting

Гуо, Лэй; Mays, Kate K.; Zhang, Yiyan; Wijaya, Derry; Betke, Margrit

doi:10.1080/15205436.2021.1898644

Cited by 22 publications

(13 citation statements)

References 46 publications

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“…This result aligns with a recent study showing that conservative audiences perceived gun violence to be less important an issue after exposure to episodically framed news from conservative media (Guo et al 2021). The reactive gesture of conservative media to progressive media might shift conservative audiences' attention to right-wing perspectives on these issues, advance views that evoke "liberal tears," and critique arguments from progressives.…”

Section: Discussionsupporting

confidence: 88%

Reactive and Asymmetric Communication Flows: Social Media Discourse and Partisan News Framing in the Wake of Mass Shootings

Zhang

Shah

Pevehouse

et al. 2022

The International Journal of Press/Politics

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Marked by both deep interconnectedness and polarization, the contemporary media system in the United States features news outlets and social media that are bound together, yet deeply divided along partisan lines. This article formally analyzes communication flows surrounding mass shootings in the hybrid and polarized U.S. media system. We begin by integrating media system literature with agenda setting and news framing theories and then conduct automated text analysis and time series modeling. After accounting for exogenous event characteristics, results show that (a) sympathy and gun control discourses on Twitter preceded news framing of gun policy more than the other way around, and (b) conservatives on Twitter and conservative media reacted to progressive discourse on Twitter, without their progressive counterparts exhibiting a similar reactiveness. Such results shed light on the influence of social media on political communication flows and confirm an asymmetry in the ways partisan media ecosystems respond to social events.

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Section: Discussionsupporting

confidence: 88%

Reactive and Asymmetric Communication Flows: Social Media Discourse and Partisan News Framing in the Wake of Mass Shootings

Zhang

Shah

Pevehouse

et al. 2022

The International Journal of Press/Politics

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“…Specifically, comments were classified using Bidirectional Encoder Representations from Transformers (BERT), a transformer-based natural language machine learning classification algorithm with outstanding performance on subtle classification tasks because it encodes both semantics and the rich latent structure of sentences ( 5 , 6 ). The superiority of BERT over other machine learning natural language classification models has been repeatedly established in varied real-world social science datasets ( 7 – 12 ).…”

Section: Methodsmentioning

confidence: 99%

Widespread use of National Academies consensus reports by the American public

Hicks

Zullo

Doshi

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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In seeking to understand how to protect the public information sphere from corruption, researchers understandably focus on dysfunction. However, parts of the public information ecosystem function very well, and understanding this as well will help in protecting and developing existing strengths. Here, we address this gap, focusing on public engagement with high-quality science-based information, consensus reports of the National Academies of Science, Engineering, and Medicine (NASEM). Attending to public use is important to justify public investment in producing and making freely available high-quality, scientifically based reports. We deploy Bidirectional Encoder Representations from Transformers (BERT), a high-performing, supervised machine learning model, to classify 1.6 million comments left by US downloaders of National Academies reports responding to a prompt asking how they intended to use the report. The results provide detailed, nationwide evidence of how the public uses open access scientifically based information. We find half of reported use to be academic—research, teaching, or studying. The other half reveals adults across the country seeking the highest-quality information to improve how they do their job, to help family members, to satisfy their curiosity, and to learn. Our results establish the existence of demand for high-quality information by the public and that such knowledge is widely deployed to improve provision of services. Knowing the importance of such information, policy makers can be encouraged to protect it.

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“…Step 5: Predict Frames with Deep Learning Once the user is satisfied with the average model performance from Step 4, they can upload an unlabeled dataset and the user's trained model can be used to predict the frames in the dataset. Our system also provides four English pretrained models on topics of gun violence trained on the gun violence frame corpus (Liu et al, 2019;Akyürek et al, 2020;Guo et al, 2021), and immigration, tobacco, and same-sex marriage trained on the media frame corpus (Card et al, 2015;Field et al, 2018).…”

Section: Related Workmentioning

confidence: 99%

OpenFraming: Open-sourced Tool for Computational Framing Analysis of Multilingual Data

Bhatia¹,

Akavoor²,

Paik³

et al. 2021

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

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When journalists cover a news story, they can cover the story from multiple angles or perspectives. These perspectives are called "frames", and usage of one frame or another may influence public perception and opinion of the issue at hand. We develop a web-based system for analyzing frames in multilingual text documents. We propose and guide users through a five-step end-toend computational framing analysis framework grounded in media framing theory in communication research. Users can use the framework to analyze multilingual text data, starting from the exploration of frames in user's corpora and through review of previous framing literature (step 1-3) to frame classification (step 4) and prediction (step 5). The framework combines unsupervised and supervised machine learning and leverages a state-of-the-art (SoTA) multilingual language model, which can significantly enhance frame prediction performance while requiring a considerably small sample of manual annotations. Through the interactive website, anyone can perform the proposed computational framing analysis, making advanced computational analysis available to researchers without a programming background and bridging the digital divide within the communication research discipline in particular and the academic community in general. The system

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What Makes Gun Violence a (Less) Prominent Issue? A Computational Analysis of Compelling Arguments and Selective Agenda Setting

Cited by 22 publications

References 46 publications

Reactive and Asymmetric Communication Flows: Social Media Discourse and Partisan News Framing in the Wake of Mass Shootings

Reactive and Asymmetric Communication Flows: Social Media Discourse and Partisan News Framing in the Wake of Mass Shootings

Widespread use of National Academies consensus reports by the American public

OpenFraming: Open-sourced Tool for Computational Framing Analysis of Multilingual Data

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