On the Influence of Twitter Trolls during the 2016 US Presidential Election
Date Issued
October 1, 2019
Abstract
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 and the impact they had 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 before they were
deleted by Twitter. 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 as part of the
investigation on the foreign interference in the 2016 US election. These data
serve as ground-truth identifier of troll users in our dataset. Using graph
analysis techniques we qualify the diffusion cascades of web and media context
that have been shared by the troll accounts. We present strong evidence that
authentic users were the source of the viral cascades. Although the trolls were
participating in the viral cascades, they did not have a leading role in them
and only four troll accounts were truly influential.
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 and the impact they had 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 before they were
deleted by Twitter. 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 as part of the
investigation on the foreign interference in the 2016 US election. These data
serve as ground-truth identifier of troll users in our dataset. Using graph
analysis techniques we qualify the diffusion cascades of web and media context
that have been shared by the troll accounts. We present strong evidence that
authentic users were the source of the viral cascades. Although the trolls were
participating in the viral cascades, they did not have a leading role in them
and only four troll accounts were truly influential.
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