Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/106792
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Title: How Elites Invigorate Emotionality and Extremity in Digital Networks
Authors: Au, A 
Issue Date: 2024
Source: Social science computer review, First published online April 15, 2024, OnlineFirst, https://doi.org/10.1177/08944393241247427
Abstract: The October 2017 Las Vegas shooting was the deadliest shooting in modern American history, but little scholarship has examined the public uproar in its wake, particularly in digital networks. Drawing on a corpus of 100,000 public Tweets and 1,119,638 unique words written in reaction to the shooting, this article addresses this lacuna by investigating the topics of reactions and their linkages with elites. This article theorizes that elites invigorate the emotionality of public reactions and broker the connection between discursive and affective content in digital networks. The results show that Tweets engaging with elites expressed statistically greater emotionality and extremity in emotional valences compared to Tweets written independent of elites. Additionally, this article identifies variations in the discursive themes invoked based on the types of elites. Mentions of non-political elites drew on themes about expressive support and depictions of the immediate environment with little emotional extremity. By contrast, mentions of political elites drew on themes about broader policy debates on gun ownership laws and adherent policy reforms. Unlike with non-political elites, mentions of political elites also exhibited greater extremity in negative emotional valences, reflective of increasing polarization in American politics.
Keywords: digital networks
elites
emotions
extremity
las vegas shooting
public debate
Publisher: Sage Publications, Inc.
Journal: Social science computer review 
ISSN: 0894-4393
EISSN: 1552-8286
DOI: 10.1177/08944393241247427
Rights: This is the accepted version of the publication Au, A. (2024). How Elites Invigorate Emotionality and Extremity in Digital Networks. Social Science Computer Review, 0(0). Copyright © 2024 (Copyright Holder). DOI: 10.1177/08944393241247427.
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