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Measuring Violence: A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest

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Measuring Violence: A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest. / Rossi, Luca; Neumayer, Christina; Henrichsen, Jesper; Beck, Lucas.

In: Social Science Computer Review, 31.01.2022.

Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

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@article{02a52d4f8d8c440aba90b45237b9afae,
title = "Measuring Violence: A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest",
abstract = "This research quantitatively investigates the impact of violence on the propagation of images in social media in the context of political protest. Using a computational approach, we measure the relative violence of a large set of images shared on Twitter during the protests against the G20 summit in Frankfurt am Main in 2017. This allows us to investigate if more violent content is shared more times and faster than less violent content on Twitter, and if different online communities can be characterized by the level of violence of the visual content they share. The results show that the level of violence in an image tweet does not correlate with the number of retweets and mentions it receives that the time to retweet is marginally lower for image tweets containing a high level of violence and that the level of violence in image tweets differs between communities.",
keywords = "digital media, image recognition, political participation, political science",
author = "Luca Rossi and Christina Neumayer and Jesper Henrichsen and Lucas Beck",
year = "2022",
month = jan,
day = "31",
language = "English",
journal = "Social Science Computer Review",
issn = "0894-4393",
publisher = "SAGE Publications",

}

RIS

TY - JOUR

T1 - Measuring Violence: A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest

AU - Rossi, Luca

AU - Neumayer, Christina

AU - Henrichsen, Jesper

AU - Beck, Lucas

PY - 2022/1/31

Y1 - 2022/1/31

N2 - This research quantitatively investigates the impact of violence on the propagation of images in social media in the context of political protest. Using a computational approach, we measure the relative violence of a large set of images shared on Twitter during the protests against the G20 summit in Frankfurt am Main in 2017. This allows us to investigate if more violent content is shared more times and faster than less violent content on Twitter, and if different online communities can be characterized by the level of violence of the visual content they share. The results show that the level of violence in an image tweet does not correlate with the number of retweets and mentions it receives that the time to retweet is marginally lower for image tweets containing a high level of violence and that the level of violence in image tweets differs between communities.

AB - This research quantitatively investigates the impact of violence on the propagation of images in social media in the context of political protest. Using a computational approach, we measure the relative violence of a large set of images shared on Twitter during the protests against the G20 summit in Frankfurt am Main in 2017. This allows us to investigate if more violent content is shared more times and faster than less violent content on Twitter, and if different online communities can be characterized by the level of violence of the visual content they share. The results show that the level of violence in an image tweet does not correlate with the number of retweets and mentions it receives that the time to retweet is marginally lower for image tweets containing a high level of violence and that the level of violence in image tweets differs between communities.

KW - digital media

KW - image recognition

KW - political participation

KW - political science

M3 - Journal article

JO - Social Science Computer Review

JF - Social Science Computer Review

SN - 0894-4393

ER -

ID: 86530642