Evolution of online user behavior during a social upheaval

Varol, Onur; Ferrara, Emilio; Ogan, Christine; Menczer, Filippo; Flammini, Alessandro

doi:10.1145/2615569.2615699

Cited by 90 publications

(115 citation statements)

References 31 publications

(43 reference statements)

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“…Social media have helped foster democratic conversation about social and political issues: from the Arab Spring [31], to Occupy Wall Street movements [16,17] and other civil protests [30,55], Twitter WWW'18, April 2018, Lyon, FR 2018. ACM ISBN 978-x-xxxx-xxxx-x/YY/MM.…”

Section: Introductionmentioning

confidence: 99%

Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign

Badawy¹,

Ferrara²,

Lerman³

2018

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

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267

212

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Until recently, social media was seen to promote democratic discourse on social and political issues. However, this powerful communication platform has come under scrutiny for allowing hostile actors to exploit online discussions in an attempt to manipulate public opinion. A case in point is the ongoing U.S. Congress investigation of Russian interference in the 2016 U.S. election campaign, with Russia accused of, among other things, using trolls (malicious accounts created for the purpose of manipulation) and bots (automated accounts) to spread misinformation and politically biased information. In this study, we explore the effects of this manipulation campaign, taking a closer look at users who re-shared the posts produced on Twitter by the Russian troll accounts publicly disclosed by U.S. Congress investigation. We collected a dataset with over 43 million elections-related posts shared on Twitter between September 16 and October 21, 2016 by about 5.7 million distinct users. This dataset included accounts associated with the identified Russian trolls. We use label propagation to infer the ideology of all users based on the news sources they shared. This method enables us to classify a large number of users as liberal or conservative with precision and recall above 90%. Conservatives retweeted Russian trolls about 31 times more often than liberals and produced 36 times more tweets. Additionally, most retweets of troll content originated from two Southern states: Tennessee and Texas. Using state-of-the-art bot detection techniques, we estimated that about 4.9% and 6.2% of liberal and conservative users respectively were bots. Text analysis on the content shared by trolls reveals that they had a mostly conservative, pro-Trump agenda. Although an ideologically broad swath of Twitter users were exposed to Russian Trolls in the period leading up to the 2016 U.S. Presidential election, it was mainly conservatives who helped amplify their message.

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Section: Introductionmentioning

confidence: 99%

Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign

Badawy¹,

Ferrara²,

Lerman³

2018

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

Self Cite

267

212

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“…For example, only three out of ten tweets relating to events in Egypt were posted by those on the ground, whereas approximately nine out of ten tweets relating to Gezi Park were posted from Turkey, with a similar proportion of tweets being written in Turkish. About half of the tweets were located to Istanbul specifically, further suggesting that the target was a Turkish audience and not global publicity (Devitt, 2014;Varol et al, 2014).…”

Section: Context For the Studymentioning

confidence: 99%

“…Tweets flooded in from all over the world about the Gezi Park protests, out of which nearly 15% of the tweets were from other countries (Varol, et al, 2014;Barberá, 2013). The Gezi Park protests received both support and opposition from members of the Turkish diaspora, with others choosing to remain silent.…”

Section: Context For the Studymentioning

confidence: 99%

Turkish diasporic responses to the Taksim Square protests: Legacy media and social media uses in Belgium, the Netherlands and Germany

Giglou

d’Haenens

Ogan

2017

Telematics and Informatics

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The Gezi Park movement which enveloped Turkey in the early summer of 2013 provided another opportunity for examining the role played by social media during times of mass social upheaval. Based on an offline and online survey of 967 people of Turkish origin living in these countries, we will test how traditional and social media has influenced the participation of the members of the Turkish diaspora in Belgium, Germany and the Netherlands in the protests in Istanbul's Taksim Gezi Square. This study will also investigate how living in Europe can influence the behavior and attitudes of the sampled individuals from the Turkish Diaspora of Germany, Belgium and Netherlands in the time span when the Taksim Gezi Park demonstration took place. Our results make it clear that social media was used by those who supported the protest movement, while those who opposed the protest movement primarily used or followed traditional sources of media, including Turkish and European television.Furthermore, supporters amongst the diaspora for the Gezi-protests were primarily active in accruing social capital through bonding and social networking among those who belong to the Turkish diaspora under the guise of the Gezi park protests. Finally, a significant number of the supporters of the protests in the three countries took part in several different means of supporting the movement, including: disseminating awareness about the Gezi protests through social media, engaging in meetings, and in some cases, even cutting off contact from friends and acquaintances whom did not share their support for the protest movement.

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“…Examples of empirical works concerned with these questions include geographic and temporal patterns in social movements (Conover et al, 2013b;Conover et al, 2013a;Varol et al, 2014), the polarization of online political discourse (Conover et al, 2011b;Conover et al, 2011a;Conover et al, 2012), the use of social media data to predict election outcomes (DiGrazia et al, 2013) and stock market movements (Bollen, Mao & Zeng, 2011), the geographic diffusion of trending topics (Ferrara et al, 2013), and the lifecycle of information in the attention economy (Ciampaglia, Flammini & Menczer, 2015).…”

Section: Introductionmentioning

confidence: 99%

OSoMe: the IUNI observatory on social media

Davis

Ciampaglia

Aiello

et al. 2016

PeerJ Computer Science

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The study of social phenomena is becoming increasingly reliant on big data from online social networks. Broad access to social media data, however, requires software development skills that not all researchers possess. Here we present the IUNI Observatory on Social Media, an open analytics platform designed to facilitate computational social science. The system leverages a historical, ongoing collection of over 70 billion public messages from Twitter. We illustrate a number of interactive open-source tools to retrieve, visualize, and analyze derived data from this collection. The Observatory,

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Evolution of online user behavior during a social upheaval

Cited by 90 publications

References 31 publications

Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign

Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign

Turkish diasporic responses to the Taksim Square protests: Legacy media and social media uses in Belgium, the Netherlands and Germany

OSoMe: the IUNI observatory on social media

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