2019
DOI: 10.1111/ajps.12436
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Social Networks and Protest Participation: Evidence from 130 Million Twitter Users

Abstract: Pinning down the role of social ties in the decision to protest has been notoriously elusive, largely due to data limitations. Social media and their global use by protesters offer an unprecedented opportunity to observe real-time social ties and online behavior, though often without an attendant measure of real-world behavior. We collect data on Twitter activity during the 2015 Charlie Hebdo protest in Paris, which, unusually, record real-world protest attendance and network structure measured beyond egocentr… Show more

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Cited by 80 publications
(62 citation statements)
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“…Müller and Schwarz exploit Facebook and Internet outages(Müller & Schwarz, 2019a) and the rise of Donald Trump together with Twitter usage(Müller & Schwarz, 2019b) to show that social media increases hate crimes in Germany and the US, respectively. Bursztyn, Egorov, Enikolopov, and Petrova (2019) also find that social media influences the rate of hate crimes in Russia.4Guriev, Melnikov, and Zhuravskaya (2019) show that increased access to 3G networks reduced government approval in a sample of 116 countries and, in European democracies, the vote shares of antiestablishment populist parties.5 One paper that goes beyond documenting the uses of social networks to evaluate their impact isLarson, Nagler, Ronen, and Tucker (2019), who collect data on Twitter activity during the 2015 Charlie Hebdo protests in Paris, recording both real-world protest attendance and social network structure. They show that the protesters are significantly more connected to one another relative to comparable Twitter users.…”
mentioning
confidence: 99%
“…Müller and Schwarz exploit Facebook and Internet outages(Müller & Schwarz, 2019a) and the rise of Donald Trump together with Twitter usage(Müller & Schwarz, 2019b) to show that social media increases hate crimes in Germany and the US, respectively. Bursztyn, Egorov, Enikolopov, and Petrova (2019) also find that social media influences the rate of hate crimes in Russia.4Guriev, Melnikov, and Zhuravskaya (2019) show that increased access to 3G networks reduced government approval in a sample of 116 countries and, in European democracies, the vote shares of antiestablishment populist parties.5 One paper that goes beyond documenting the uses of social networks to evaluate their impact isLarson, Nagler, Ronen, and Tucker (2019), who collect data on Twitter activity during the 2015 Charlie Hebdo protests in Paris, recording both real-world protest attendance and social network structure. They show that the protesters are significantly more connected to one another relative to comparable Twitter users.…”
mentioning
confidence: 99%
“…In the digital era, the efficiency of online networks is vital in spreading protest messages and linking offline participants (Barberá et al., ; Larson et al., ). Social media activities can also contribute to the offline diffusion of movements such as Occupy Wall Street (Vasi and Suh, ).…”
Section: Media and Protest In Advanced Democracies And Beyondmentioning
confidence: 99%
“…Second, using much less data markedly lowers the cost of data collection. For example, Larson et al (2016) collect the Twitter social network out to two degrees (the connections' connections) of 1,764 accounts from France, resulting in 199,126,639 additional nodes (111,618.07 connections per original account). The first-degree crawl this paper performs for the 21 activist accounts (discussed shortly) generates 90,863.52 connections per account.…”
Section: Ncc Instead Of Indegree Centralitymentioning
confidence: 99%
“…While Larson et al (2016) do not undertake centrality analysis because it is not the focus of their research question, note that they would still have biased results because they do not have complete data. A comparison of sample strategies on four different networks finds that each sampling procedure requires a large network sample (over 50% of all nodes) before that sample's network characteristics converge to the full network's value (Lee et al 2006).…”
Section: Ncc Instead Of Indegree Centralitymentioning
confidence: 99%
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