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• W3046363476 abstract "Abstract This study reveals a shift of gun-related narratives created by two ideological groups during three high-profile mass shootings in the United States across the years from 2016 to 2018. It utilizes large-scale, longitudinal social media traces from over 155,000 ideology-identifiable Twitter users. The study design leveraged both the linguistic dictionary approach as well as thematic coding inspired by Narrative Policy Framework, which allows for statistical and qualitative comparison. We found several distinctive narrative characteristics between the two ideology groups in response to the shooting events—two groups differed by how they incorporated linguistic and narrative features in their tweets in terms of policy stance, attribution (how one believed to be the problem, the cause or blame, and the solution), the rhetoric employed, and emotion throughout the incidents. The findings suggest how shooting events may penetrate the public discursive processes that had been previously dominated by existing ideological references and may facilitate discussions beyond ideological identities. Overall, in the wake of mass shooting events, the tweets adhering to the majority policy stance within a camp declined, whereas the proportion of mixed or flipped stance tweets increased. Meanwhile, more tweets were observed to express causal reasoning of a held policy stance, and a different pattern in the use of rhetoric schemes, such as the decline of provocative ridicule, emerged. The shifting patterns in users’ narratives coincide with the two groups distinctive emotional response revealed in text. These findings offer insights into the opportunity to reconcile conflicts and the potential for creating civic technologies to improve the interpretability of linguistic and narrative signals and to support diverse narratives and framing." @default.
• W3046363476 created "2020-08-07" @default.
• W3046363476 creator A5020014094 @default.
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• W3046363476 date "2020-08-03" @default.
• W3046363476 modified "2023-10-12" @default.
• W3046363476 title "The dynamics of Twitter users’ gun narratives across major mass shooting events" @default.
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• W3046363476 doi "https://doi.org/10.1057/s41599-020-00533-8" @default.
• W3046363476 hasPublicationYear "2020" @default.
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