Are social bots on Twitter political actors? Empirical evidence from a Ukrainian social botnet

Simon Hegelich; Dietmar Janetzko

Are social bots on Twitter political actors? Empirical evidence from a Ukrainian social botnet

Simon Hegelich, Dietmar Janetzko

Associate Professorship of Political Data Science

Cologne Business School

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

69 Scopus citations

Abstract

A considerable amount of data in social networks like Twitter is not generated by humans but by automatic programs (bots). Some of these bots are mimicking humans (social-bots) and can hardly be identified. In this article, we analyze a social botnet involved in the Ukrainian/Russian conflict. Based on text mining and unsupervised learning, we can identify three different behaviors: mimicry, window dressing, and reverberation.

Original language	English
Title of host publication	Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016
Publisher	AAAI Press
Pages	579-582
Number of pages	4
ISBN (Electronic)	9781577357582
State	Published - 2016
Event	10th International Conference on Web and Social Media, ICWSM 2016 - Cologne, Germany Duration: 17 May 2016 → 20 May 2016

Publication series

Name	Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016

Conference

Conference	10th International Conference on Web and Social Media, ICWSM 2016
Country/Territory	Germany
City	Cologne
Period	17/05/16 → 20/05/16

Cite this

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title = "Are social bots on Twitter political actors? Empirical evidence from a Ukrainian social botnet",

abstract = "A considerable amount of data in social networks like Twitter is not generated by humans but by automatic programs (bots). Some of these bots are mimicking humans (social-bots) and can hardly be identified. In this article, we analyze a social botnet involved in the Ukrainian/Russian conflict. Based on text mining and unsupervised learning, we can identify three different behaviors: mimicry, window dressing, and reverberation.",

author = "Simon Hegelich and Dietmar Janetzko",

note = "Publisher Copyright: {\textcopyright} Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 10th International Conference on Web and Social Media, ICWSM 2016 ; Conference date: 17-05-2016 Through 20-05-2016",

year = "2016",

language = "English",

series = "Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016",

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Hegelich, S & Janetzko, D 2016, Are social bots on Twitter political actors? Empirical evidence from a Ukrainian social botnet. in Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016. Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016, AAAI Press, pp. 579-582, 10th International Conference on Web and Social Media, ICWSM 2016, Cologne, Germany, 17/05/16.

Are social bots on Twitter political actors? Empirical evidence from a Ukrainian social botnet. / Hegelich, Simon; Janetzko, Dietmar.
Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016. AAAI Press, 2016. p. 579-582 (Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Janetzko, Dietmar

PY - 2016

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N2 - A considerable amount of data in social networks like Twitter is not generated by humans but by automatic programs (bots). Some of these bots are mimicking humans (social-bots) and can hardly be identified. In this article, we analyze a social botnet involved in the Ukrainian/Russian conflict. Based on text mining and unsupervised learning, we can identify three different behaviors: mimicry, window dressing, and reverberation.

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BT - Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016

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Are social bots on Twitter political actors? Empirical evidence from a Ukrainian social botnet

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