It is a widely accepted fact that state-sponsored Twitter accounts operated during the 2016 US presidential election, spreading millions of tweets with misinformation and inflammatory political content. Whether these social media campaigns of the so-called "troll" accounts were able to manipulate public opinion is still in question. Here, we aim to quantify the influence of troll accounts on Twitter by analyzing 152.5 million tweets from 9.9 million users , including 822 troll accounts . The data collected during the US election campaign, contain original troll tweets . From these data , we constructed a very large interaction graph ; a directed graph of 9.3 million nodes and 169.9 million edges . Recently, Twitter released datasets on the misinformation campaigns of 8 , 275 state-sponsored accounts linked to Russia, Iran and Venezuela. These data serve as a ground-truth identifier of troll users in our dataset. Using graph analysis techniques along with a game-theoretic centrality measure, we quantify the influence of all Twitter accounts (authentic users and trolls) on the overall information exchange as is defined by the retweet cascades. Then, we provide a global influence ranking of all Twitter accounts and we find that only four troll accounts appear in the top-1000 and only one in the top-100 . This along with other findings presents evidence that the authentic users were the driving force of virality and influence in the network  .
It is a widely accepted fact that state-sponsored Twitter accounts operated during the 2016 US presidential election, spreading millions of tweets with misinformation and inflammatory political content. Whether these social media campaigns of the so-called "troll" accounts were able to manipulate public opinion is still in question. Here, we aim to quantify the influence of troll accounts on Twitter by analyzing 152.5 million tweets from 9.9 million users . The data collected during the US election campaign, contain original tweets from 822 troll accounts which have been identified as such, based on archive data released by Twitter related to state-sponsored trolls' campaigns. Then , we constructed a very large interaction graph of 9.3 million nodes and 169.9 million edges , where using graph analysis techniques along with a game-theoretic centrality measure, we quantify the influence of all Twitter accounts on the overall information exchange as is defined by the retweet cascades. Then, we provide a global influence ranking of all Twitter accounts and we find that one troll account appears in the top-100 and four in the top-1000 . This along with other findings presents evidence that the driving force of virality and influence in the network came from regular users - users who have not been classified as trolls by Twitter. On the other hand, we find that on average, troll accounts were tens of times more influential than regular users were. Moreover, 23\% and 22\% of regular accounts in the top-100 and top-1000 respectively, have now been suspended by Twitter. This raises questions about their authenticity and practices overall, during the 2016 US presidential election .
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, including 822 troll accounts
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troll tweets . From these data
tweets from 822 troll accounts which have been identified as such, based on archive data released by Twitter related to state-sponsored trolls' campaigns. Then
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; a directed graph
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. Recently, Twitter released datasets on the misinformation campaigns of 8
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275 state-sponsored accounts linked to Russia, Iran and Venezuela. These data serve as a ground-truth identifier of troll users in our dataset. Using
where using
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(authentic users and trolls)
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only four troll accounts appear in the top-1000 and only one in the top-100
one troll account appears in the top-100 and four in the top-1000
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authentic users were the
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came from regular users - users who have not been classified as trolls by Twitter. On the other hand, we find that on average, troll accounts were tens of times more influential than regular users were. Moreover, 23\% and 22\% of regular accounts in the top-100 and top-1000 respectively, have now been suspended by Twitter. This raises questions about their authenticity and practices overall, during the 2016 US presidential election