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Multidimensional Mappings of Political Accounts for Malicious Political Socialbot Identification: Exploring Social Networks, Geographies, and Strategic Messaging

Multidimensional Mappings of Political Accounts for Malicious Political Socialbot Identification: Exploring Social Networks, Geographies, and Strategic Messaging

Shalin Hai-Jew
Copyright: © 2019 |Pages: 86
ISBN13: 9781522559276|ISBN10: 1522559272|ISBN13 Softcover: 9781522587439|EISBN13: 9781522559283
DOI: 10.4018/978-1-5225-5927-6.ch012
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MLA

Hai-Jew, Shalin. "Multidimensional Mappings of Political Accounts for Malicious Political Socialbot Identification: Exploring Social Networks, Geographies, and Strategic Messaging." Global Cyber Security Labor Shortage and International Business Risk, edited by Bryan Christiansen and Agnieszka Piekarz, IGI Global, 2019, pp. 263-348. https://doi.org/10.4018/978-1-5225-5927-6.ch012

APA

Hai-Jew, S. (2019). Multidimensional Mappings of Political Accounts for Malicious Political Socialbot Identification: Exploring Social Networks, Geographies, and Strategic Messaging. In B. Christiansen & A. Piekarz (Eds.), Global Cyber Security Labor Shortage and International Business Risk (pp. 263-348). IGI Global. https://doi.org/10.4018/978-1-5225-5927-6.ch012

Chicago

Hai-Jew, Shalin. "Multidimensional Mappings of Political Accounts for Malicious Political Socialbot Identification: Exploring Social Networks, Geographies, and Strategic Messaging." In Global Cyber Security Labor Shortage and International Business Risk, edited by Bryan Christiansen and Agnieszka Piekarz, 263-348. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-5927-6.ch012

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Abstract

Malicious political socialbots used to sway public opinion regarding the U.S. government and its functions have been identified as part of a larger information warfare effort by the Russian government. This work asks what is knowable from a web-based sleuthing approach regarding the following four factors: 1) the ability to identify malicious political socialbot accounts based on their ego neighborhoods at 1, 1.5, and 2 degrees; 2) the ability to identify malicious political socialbot accounts based on the claimed and linked geographical locations of their accounts, their ego neighborhoods, and their #hashtag networks; 3) the ability to identify malicious political socialbot accounts based on their strategic messaging (content, sentiment, and language structures) on respective social media platforms; and 4) the ability to identify and describe “maliciousness” in malicious political socialbot accounts based on observable behaviors on that account on three social media platform types: (a) microblogging, (b) social networking, and (c) crowd-sourced encyclopedia content sharing.

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