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The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack

We describe the evolution of a stereotype as it emerged in tweets about the Charlie Hebdo terrorist attack in Paris in early 2015. Our focus is on terms associated with the Muslim community and the Islamic world. The data (400k tweets) were collected via Twitter streaming API and consisted of tweets...

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Autores principales: Marzouki, Yousri, Barach, Eliza, Srinivasan, Vidhushini, Shaikh, Samira, Feldman, Laurie Beth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413988/
https://www.ncbi.nlm.nih.gov/pubmed/32793820
http://dx.doi.org/10.1016/j.heliyon.2020.e04311
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author Marzouki, Yousri
Barach, Eliza
Srinivasan, Vidhushini
Shaikh, Samira
Feldman, Laurie Beth
author_facet Marzouki, Yousri
Barach, Eliza
Srinivasan, Vidhushini
Shaikh, Samira
Feldman, Laurie Beth
author_sort Marzouki, Yousri
collection PubMed
description We describe the evolution of a stereotype as it emerged in tweets about the Charlie Hebdo terrorist attack in Paris in early 2015. Our focus is on terms associated with the Muslim community and the Islamic world. The data (400k tweets) were collected via Twitter streaming API and consisted of tweets that contained at least one of 16 hashtags associated with the Charlie Hebdo attack (e.g., #JeSuisCharlie, #IAmCharlie, #ParisAttacks), collected between January 14th and February 9th. From these data, we generated pairwise co-occurrence frequencies between key words such as “Islam”, “Muslim(s)”, “Arab(s)”, and “The Prophet” and possible associates such as: “terrorism”, “terror”, “terrorist(s)”, “kill(ed)”, “free”, “freedom” and “love”. We use changes in frequency of co-occurring words to define ways in which acute negative and positive stereotypes towards Muslims and Islam arise and evolve in three phases during the period of interest. We identify a positively-valenced backlash in a subset of tweets associated with the “origins of Islam”. Results depict the emergence and transformation of implicit online stereotypes related to Islam from naturally occurring social media data and how pro-as well as anti-Islam online small-world networks evolve in response to a terrorist attack.
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spelling pubmed-74139882020-08-12 The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack Marzouki, Yousri Barach, Eliza Srinivasan, Vidhushini Shaikh, Samira Feldman, Laurie Beth Heliyon Article We describe the evolution of a stereotype as it emerged in tweets about the Charlie Hebdo terrorist attack in Paris in early 2015. Our focus is on terms associated with the Muslim community and the Islamic world. The data (400k tweets) were collected via Twitter streaming API and consisted of tweets that contained at least one of 16 hashtags associated with the Charlie Hebdo attack (e.g., #JeSuisCharlie, #IAmCharlie, #ParisAttacks), collected between January 14th and February 9th. From these data, we generated pairwise co-occurrence frequencies between key words such as “Islam”, “Muslim(s)”, “Arab(s)”, and “The Prophet” and possible associates such as: “terrorism”, “terror”, “terrorist(s)”, “kill(ed)”, “free”, “freedom” and “love”. We use changes in frequency of co-occurring words to define ways in which acute negative and positive stereotypes towards Muslims and Islam arise and evolve in three phases during the period of interest. We identify a positively-valenced backlash in a subset of tweets associated with the “origins of Islam”. Results depict the emergence and transformation of implicit online stereotypes related to Islam from naturally occurring social media data and how pro-as well as anti-Islam online small-world networks evolve in response to a terrorist attack. Elsevier 2020-08-06 /pmc/articles/PMC7413988/ /pubmed/32793820 http://dx.doi.org/10.1016/j.heliyon.2020.e04311 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Marzouki, Yousri
Barach, Eliza
Srinivasan, Vidhushini
Shaikh, Samira
Feldman, Laurie Beth
The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack
title The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack
title_full The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack
title_fullStr The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack
title_full_unstemmed The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack
title_short The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack
title_sort dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the charlie hebdo terrorist attack
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413988/
https://www.ncbi.nlm.nih.gov/pubmed/32793820
http://dx.doi.org/10.1016/j.heliyon.2020.e04311
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