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Title: On the Influence of Twitter Trolls during the 2016 US Presidential Election
Authors: Salamanos, Nicos 
Jensen, Michael J. 
He, Xinlei 
Chen, Yang 
Sirivianos, Michael 
Major Field of Science: Engineering and Technology
Field Category: Electrical Engineering - Electronic Engineering - Information Engineering
Keywords: Computer Science;Social and Information Networks
Issue Date: 1-Oct-2019
Project: Cyber security cOmpeteNce fOr Research anD Innovation 
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.
Description: With this version, we are correcting an error in the Acknowledgments regarding the research funding that supports this work. The correct one is the European Union's Horizon 2020 Research and Innovation program under the Cybersecurity CONCORDIA project (Grant Agreement No. 830927)
Type: Article
Affiliation : Cyprus University of Technology 
University of Canberra 
Fudan University 
Appears in Collections:Άρθρα/Articles

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