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https://doi.org/10.31234/osf.i...
Article . 2018 . Peer-reviewed
License: CC BY
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PsyArXiv
Preprint . 2018
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Characterizing the Internet Research Agency’s Social Media Operations During the 2016 U.S. Presidential Election using Linguistic Analyses

Authors: Ryan L. Boyd; Alexander Spangher; Adam Fourney; Besmira Nushi; Gireeja Ranade; James Pennebaker; Eric Horvitz;

Characterizing the Internet Research Agency’s Social Media Operations During the 2016 U.S. Presidential Election using Linguistic Analyses

Abstract

Converging investigations on the part of multiple agencies/agents have provided overwhelming evidence for Russian interference in the 2016 U.S. presidential election. As a part (and consequence) of recent reports, multiple datasets that capture actions taken by actors of the Internet Research Agency (IRA), have been released to the public. In the cur-rent paper, we present and abridged report of several preliminary forensic analyses of Facebook ad data and Twitter troll accounts that were run by the IRA during the election cycle. Through the use of language analysis, we characterize the evolution of IRA content over the course of the election cycle, providing a basis for understanding how left- and right-leaning ideologies were differentially targeted to spread enmity among the American electorate. Additionally, through an analysis of syntactic constructions, we find that the content produced by the IRA on Twitter was linguistically unique from a control sample of English-speaking Twitter accounts. Altogether, our findings suggest that the IRA’s operations were largely unsophisticated and “low-budget” in nature, with no serious attempts at point-of-origin obfuscation being taken.

Keywords

bepress|Social and Behavioral Sciences|Psychology, bepress|Social and Behavioral Sciences|Public Affairs, Public Policy and Public Administration|Science and Technology Policy, PsyArXiv|Social and Behavioral Sciences|Forensic and Legal Psychology, bepress|Law|Law and Psychology, PsyArXiv|Social and Behavioral Sciences|Quantitative Methods|Computational Modeling, bepress|Social and Behavioral Sciences|Psychology|Quantitative Psychology, PsyArXiv|Social and Behavioral Sciences, PsyArXiv|Social and Behavioral Sciences|Quantitative Methods|Science and Technology Policy, PsyArXiv|Social and Behavioral Sciences|Psychology, other, bepress|Social and Behavioral Sciences, PsyArXiv|Social and Behavioral Sciences|Quantitative Methods, bepress|Social and Behavioral Sciences|Linguistics, PsyArXiv|Social and Behavioral Sciences|Linguistics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Top 10%
Top 10%
Top 10%
hybrid