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

Research output: Contribution to journal › Journal article › Research › peer-review

Standard

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

In: Social Science Computer Review, Vol. 41, No. 3, 2023, p. 905–925.

Research output: Contribution to journal › Journal article › Research › peer-review

Harvard

Rossi, L, Neumayer, C, Henrichsen, J & Beck, LK 2023, 'Measuring Violence: A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest', Social Science Computer Review, vol. 41, no. 3, pp. 905–925. https://doi.org/10.1177/08944393211055429

APA

Rossi, L., Neumayer, C., Henrichsen, J., & Beck, L. K. (2023). Measuring Violence: A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest. Social Science Computer Review, 41(3), 905–925. https://doi.org/10.1177/08944393211055429

Vancouver

Rossi L, Neumayer C, Henrichsen J, Beck LK. Measuring Violence: A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest. Social Science Computer Review. 2023;41(3):905–925. https://doi.org/10.1177/08944393211055429

Author

Rossi, Luca ; Neumayer, Christina ; Henrichsen, Jesper ; Beck, Lucas K. / Measuring Violence : A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest. In: Social Science Computer Review. 2023 ; Vol. 41, No. 3. pp. 905–925.

Bibtex

@article{7bd280495c3f42378c2fa8a6962ae47c,
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.",
author = "Luca Rossi and Christina Neumayer and Jesper Henrichsen and Beck, {Lucas K.}",
year = "2023",
doi = "10.1177/08944393211055429",
language = "English",
volume = "41",
pages = "905–925",
journal = "Social Science Computer Review",
issn = "0894-4393",
publisher = "SAGE Publications",
number = "3",

}

RIS

TY - JOUR

T1 - Measuring Violence

T2 - 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 K.

PY - 2023

Y1 - 2023

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.

UR - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3938168

U2 - 10.1177/08944393211055429

DO - 10.1177/08944393211055429

M3 - Journal article

VL - 41

SP - 905

EP - 925

JO - Social Science Computer Review

JF - Social Science Computer Review

SN - 0894-4393

IS - 3

ER -

ID: 306310980