Perils and Challenges of Social Media and Election Manipulation Analysis: The 2018 US Midterms

Ashok, Deb; Luca, Luceri; Adam, Badawy; Emilio, Ferrara (17 May 2019). Perils and Challenges of Social Media and Election Manipulation Analysis: The 2018 US Midterms. In: WWW '19 Companion. Proceedings of The 2019 World Wide Web Conference (pp. 237-247). New York: ACM 10.1145/3308560.3316486

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One of the hallmarks of a free and fair society is the ability to conduct a peaceful and seamless transfer of power from one leader to another. Democratically, this is measured in a citizen population’s trust in the electoral system of choosing a representative government. In view of the well documented issues of the 2016 US Presidential election, we conducted an in-depth analysis of the 2018 US Midterm elections looking specifically for voter fraud or suppression. The Midterm election occurs in the middle of a 4 year presidential term. For the 2018 midterms, 35 Senators and all the 435 seats in the House of Representatives were up for reelection, thus, every congressional district and practically every state had a federal election. In order to collect election related tweets, we analyzed Twitter during the month prior to, and the two weeks following, the November 6, 2018 election day. In a targeted analysis to detect statistical anomalies or election interference, we identified several biases that can lead to wrong conclusions. Specifically, we looked for divergence between actual voting outcomes and instances of the #ivoted hashtag on the election day. This analysis highlighted three states of concern: New York, California, and Texas. We repeated our analysis discarding malicious accounts, such as socialbots. Upon further inspection and against a backdrop of collected general election-related tweets, we identified some confounding factors, such as population bias, or bot and political ideology inference, that can lead to false conclusions. We conclude by providing an in-depth discussion of the perils and challenges of using socialmedia data to explore questions about election manipulation.

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

08 Faculty of Science > Institute of Computer Science (INF) > Communication and Distributed Systems (CDS)
08 Faculty of Science > Institute of Computer Science (INF)

Subjects:

000 Computer science, knowledge & systems
500 Science > 510 Mathematics

ISBN:

978-1-4503-6675-5

Series:

Proceedings of The 2019 World Wide Web Conference

Publisher:

ACM

Language:

English

Submitter:

Dimitrios Xenakis

Date Deposited:

17 Jul 2019 15:35

Last Modified:

23 Feb 2021 22:40

Publisher DOI:

10.1145/3308560.3316486

BORIS DOI:

10.7892/boris.131226

URI:

https://boris.unibe.ch/id/eprint/131226

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