Coordinated campaigns are used to influence and manipulate social media platforms and their users, a critical challenge to the free exchange of information online. Here we introduce a general  network-based framework to uncover groups of accounts that are likely coordinated. The proposed method construct coordination networks based on arbitrary behavioral traces shared among accounts. We present five case studies of influence campaigns  in the diverse contexts of U.S. elections, Hong Kong protests, the Syrian civil war, and cryptocurrencies . In each of these cases, we detect networks of coordinated Twitter accounts by examining their identities, images, hashtag sequences, retweets, and temporal patterns. The proposed framework proves to be broadly applicable to uncover different kinds of coordination across information warfare scenarios.
Coordinated campaigns are used to influence and manipulate social media platforms and their users, a critical challenge to the free exchange of information online. Here we introduce a general , unsupervised network-based methodology to uncover groups of accounts that are likely coordinated. The proposed method constructs coordination networks based on arbitrary behavioral traces shared among accounts. We present five case studies of influence campaigns , four of which in the diverse contexts of U.S. elections, Hong Kong protests, the Syrian civil war, and cryptocurrency manipulation . In each of these cases, we detect networks of coordinated Twitter accounts by examining their identities, images, hashtag sequences, retweets, or temporal patterns. The proposed approach proves to be broadly applicable to uncover different kinds of coordination across information warfare scenarios.
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, unsupervised
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framework
methodology
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construct
constructs
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, four of which
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cryptocurrencies
cryptocurrency manipulation
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and
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framework
approach