Communication strategies of social bots: models of influence on the audience
DOI:
https://doi.org/10.21638/spbu12.2019.203Abstract
The article analyzes a phenomenon of social bots that is actively discussed in the literature. Researchers study the use of social bots in different areas and their growing power of manipulative influence. The authors have accomplished the following goals: 1) analyzed the most common approaches to the typology of botnets, 2) designed new approach to the typology of bots, associated with the peculiarities of their impact on the potential audience within a specific communication strategy, 3) developed parameters to describe different models of influence on the audience, 4) verified hypothesis using an example of a case study that analyzed two botnets in the “VKontakte” social network detected with the help of the author's technique. The results of the study. The authors identify the following parameters of the impact of bots on a potential audience: 1) the number of technological accounts in a botnet, 2) intensity of publication activities. These two parameters combined help identify extensive and intensive models of influence on a potential audience. In addition, they help find differences in the implementation of an attraction function. One botnet illustrates an extensive model of influence; the other shows an intensive model. The authors suggest that the choice of an impact model may depend on a botnet’s thematic focus and a type of a potential audience. In the future, to extend the examination of botnets’ communication strategies, the authors plan to add and analyze other parameters yet to be determined.
Keywords:
bots, botnets, typology of bots, methods of detecting botnets, intensive and extensive models
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References
Литература
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References
Bessi A., Ferrara E. Social Bots Distort the 2016 US Presidential Election Online Discussion. First Monday, 2016, vol. 21, is. 11. URL: https://ssrn.com/abstract=2982233 (accessed on 15.03.2019).
Forelle M. C., Howard P. N., Monroy-Hernandez A., Savage S. Political bots and the manipulation of public opinion in Venezuela, Oxford, UK. Project on Computational Propaganda, 2015. URL: https://arxiv.org/ftp/arxiv/papers/1507/1507.07109.pdf (accessed on 15.03.2019).
Howard P. N., Bolsover G., Kollanyi B., Bradshaw S., Neudert L.-M. Junk news and bots during the U. S. Election: What were Michigan voters sharing over Twitter? Working Papers & Data Memos, Oxford, UK, Project on Computational Propaganda, 2017. URL: http://comprop.oii.ox.ac.uk/research/working-papers/junk-news-and-bots-during-the-u-s-election-what-were-michigan-voters-sharing-over-twitter/ (accessed on 15.03.2019).
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Schäfer F., Evert S., Heinrich P. Japan's 2014 General Election: Political Bots, Right-Wing Internet Activism, and Prime Minister Shinzō Abe's Hidden Nationalist Agenda. Big data, 2017, vol. 5, is. 4, pp. 294–309. doi: 10.1089/big.2017.0049
Shorey S., Howard P. N. Automation, Algorithms, and Politics. Automation: Big Data and Politics: A Research Review. International Journal of Communication, 2016, vol. 10, pp. 5032–5055. URL: http://ijoc.org/index.php/ijoc/article/view/6233/1812 (accessed on 15.03.2019).
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Waugh B., Abdinpanah M., Hashemi O., Rahman S. A., Cook D. M. The Influence and Deception of Twitter: The Authenticity of the Narrative and Slacktivism in the Australian Electoral Process. Proceedings of the 14th Australian Information Warfare Conference, Edith Cowan University, Perth, Western Australia, 2013, pp. 27–38. doi: 10.4225/75/57a849a9befb7
Williams J. A., Miller D. M. Netizens Decide 2014? A Look at Party Campaigning Online. In Japan Decides. 2nd ed. London, Palgrave Macmillan, 2016, pp. 144–152.
Woolley S. C. Automating power: Social bot interference in global politics. First Monday, 2016, vol. 21, is. 4. URL: http://firstmonday.org/article/view/6161/5300 (accessed on 15.03.2019).
Woolley S. C., Howard P. N. Automation, algorithms, and political communication, computational propaganda, and autonomous agent — Introduction. International Journal of Communication, 2016, vol. 10, pp. 4882–4890. URL: https://ijoc.org/index.php/ijoc/article/view/6298/1809 (accessed on 15.03.2019).
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Boshmaf Y., Muslukhov I., Beznosov K., Ripeanu M. The socialbot network: when bots socialize for fame and money, In Proceedings of the 27th Annual Computer Security Applications Conference, Orlando, Florida, USA. New York, 2011, pp. 93–102. doi: 10.1145/2076732.2076746
Calo R. Robotics and the Lessons of Cyberlaw. California Law Review, 2015, vol. 103, is. 3. URL: https://scholarship.law.berkeley.edu/cgi/viewcontent.cgi?article=4284&context=californialawreview (accessed on 15.03.2019).
Gorwa R., Guilbeault D. Unpacking the Social Media Bot: A Typology to Guide Research and Policy. Policy & Internet, 2018. URL: https://arxiv.org/pdf/1801.06863.pdf (accessed on 15.03.2019).
Nagaraja S., Houmansadr A., Piyawongwisal P., Singh V., Agarwal P., Borisov N. Stegobot: a covert social network botnet. In International Workshop on Information. Hiding, Berlin, Heidelberg, 2011, pp. 299–313.
Stieglitz S., Brachten F., Ross B., Jung A.-K. Do Social Bots Dream of Electric Sheep? A Categorisation of Social Media Bot Accounts. Australasian Conference on Information Systems, Hobart, Australia, 2017. URL: https://arxiv.org/ftp/arxiv/papers/1710/1710.04044.pdf (accessed on 15.03.2019).
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Published
2019-06-27
How to Cite
Vasilkova, V. V. ., Legostaeva, N. I. ., & Radushevsky, V. B. . (2019). Communication strategies of social bots: models of influence on the audience. Vestnik of Saint Petersburg University. Sociology, 12(2), 153–163. https://doi.org/10.21638/spbu12.2019.203
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Language, Culture, Communication
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Articles of "Vestnik of Saint Petersburg University. Sociology" are open access distributed under the terms of the License Agreement with Saint Petersburg State University, which permits to the authors unrestricted distribution and self-archiving free of charge.
