Extensive and Intensive Models of Botnet Influence over Target Audience

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборникенаучнаярецензирование

Выдержка

In the article, authors make an overview of existing approaches to typologization of bots and suggest their own approach for distinguishing botnets based on the influence of botnets over target audience. Using the logic of this approach, authors have performed a comparative analysis of two botnets found in the “VKontakte” social network, which revealed existence of two models of influence over target audience: extensive and intensive. Among the criteria for comparative analysis, botnets are characterized by “number of technological accounts in the botnet”, “intensity of publication activities”. Authors assume that the choice of one of these two models depends on thematic orientation of botnets, which involves different types of potential audiences.
Язык оригиналаанглийский
Название основной публикацииExtensive and Intensive Models of Botnet Influence over Target Audience
Место публикацииParis, France
Страницы252-254
Число страниц3
ИзданиеAtlantis Press
ISBN (электронное издание)978-94-6252-717-1
СостояниеОпубликовано - 26 мая 2019

Отпечаток

social network

Предметные области Scopus

  • Социальные науки (все)

Ключевые слова

  • боты
  • ботсети
  • типология ботов
  • методики выявления ботов
  • экстенсивные и интенсивные модели

Цитировать

Василькова, В. В., Легостаева, Н. И., & Радушевский, В. Б. (2019). Extensive and Intensive Models of Botnet Influence over Target Audience. В Extensive and Intensive Models of Botnet Influence over Target Audience (Atlantis Press ред., стр. 252-254). Paris, France.
Василькова, Валерия Валентиновна ; Легостаева, Наталья Игоревна ; Радушевский, Владимир Борисович. / Extensive and Intensive Models of Botnet Influence over Target Audience. Extensive and Intensive Models of Botnet Influence over Target Audience . Atlantis Press . ред. Paris, France, 2019. стр. 252-254
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title = "Extensive and Intensive Models of Botnet Influence over Target Audience",
abstract = "In the article, authors make an overview of existing approaches to typologization of bots and suggest their own approach for distinguishing botnets based on the influence of botnets over target audience. Using the logic of this approach, authors have performed a comparative analysis of two botnets found in the “VKontakte” social network, which revealed existence of two models of influence over target audience: extensive and intensive. Among the criteria for comparative analysis, botnets are characterized by “number of technological accounts in the botnet”, “intensity of publication activities”. Authors assume that the choice of one of these two models depends on thematic orientation of botnets, which involves different types of potential audiences.",
keywords = "боты, ботсети, типология ботов, методики выявления ботов, экстенсивные и интенсивные модели, bots, botnets, typology of bots, botnet detection techniques, intensive and extensive models",
author = "Василькова, {Валерия Валентиновна} and Легостаева, {Наталья Игоревна} and Радушевский, {Владимир Борисович}",
note = "[1] A. Bessi, E. Ferrara, “Social Bots Distort the 2016 US Presidential Election Online 8 Discussion”, First Monday, 2016, vol. 21(11). [2] Y. Boshmaf, I. Muslukhov, K. Beznosov, M. Ripeanu, “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. [3] R. Calo, “Robotics and the Lessons of Cyberlaw”, Cal. L. Rev., 2015, vol. 103(3). [4] E. Ferrara, O. Varol, C. Davis, F. Menczer, A. Flammini, “The rise of social bots”, Communications of the ACM, vol. 59(7), 2016, pp. 96–104. [5] A. F{\o}lstad, P.B. Brandtz{\ae}g, “Chatbots and the new world of HCI. Interactions”, vol. 24(4), July-August 2017, pp. 38-42. [6] M.C. Forelle, P.N. Howard, A. Monroy-Hernandez, S. Savage, “Political bots and the manipulation of public opinion in Venezuela”, Oxford, UK: Project on Computational Propaganda, 2015. [7] R. Gorwa, D. Guilbeault, “Unpacking the Social Media Bot: A Typology to Guide Research and Polic”,. Policy & Internet, 2018. [8] P.N. Howard, G. Bolsover, B. Kollanyi, S. Bradshaw, L.-M. Neudert, “Junk news and bots during the U.S. Election: What were Michigan voters sharing over Twitter?”, Working Papers & DataMemos. Oxford, UK: Project on Computational Propaganda, 2017. [9] P.N. Howard, S. Woolley, R. Calo, “Algorithms, bots, and political communication in the US 2016 election: The challenge of automated political communication for election law and administration”, Journal of Information Technology & Politics, vol. 15(2), 2018, pp. 81-93. [10] D. Murthy, A.B. Powell, R. Tinati, N. Anstead, L. Carr, S.J. Halford, M. Weal, “Automation, algorithms, and politics| Bots and political influence: A sociotechnical investigation of social network capital”, International Journal of Communication, vol. 10, 2016, pp. 4952–4971. [11] S. Nagaraja, A. Houmansadr, P. Piyawongwisal, V. Singh, P. Agarwal, N. Borisov, “Stegobot: a covert social network botnet”, in International Workshop on Information Hiding. Springer, Berlin, Heidelberg, 2011, pp. 299-313. [12] G. Neff, P. Nagy, “Automation, algorithms, and politics| talking to bots: symbiotic agency and the case of tay”, International Journal of Communication, vol. 10, 2016, pp. 4915–4931. [13] F. Sch{\"a}fer, S. Evert, P. Heinrich, “Japan's 2014 General Election: Political Bots, Right-Wing Internet Activism, and Prime Minister Shinzō Abe's Hidden Nationalist Agenda”, Big data, vol. 5(4), 2017, pp. 294-309. [14] S. Shorey, P.N. Howard, “Automation, Algorithms, and Politics| Automation, Big Data and Politics: A Research Review”, International Journal of Communication, vol. 10, 2016, pp. 5032–5055. [15] S. Stieglitz, F. Brachten, B. Ross, A-K. Jung, “ Do Social Bots Dream of Electric Sheep? A Categorisation of Social Media Bot Accounts”, Australasian Conference on Information Systems. Hobart, Australia, 2017. [16] M. Tsvetkova, R. Garc{\'i}a-Gavilanes, L. Floridi, T. Yasseri, “Even good bots fight: The case of Wikipedia”, PLoS ONE 12(2): e0171774, 2017. [17] B. Waugh, M. Abdinpanah, O. Hashemi, S.A. Rahman, D.M. Cook, “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. [18] J.A. Williams, D.M. Miller, “Netizens Decide 2014? A Look at Party Campaigning Online. In Japan Decides”, 2nd ed. Palgrave Macmillan, London, 2016, pp 144-152. [19] S.C. Woolley, “Automating power: Social bot interference in global politics”, First Monday, vol. 21(4), 2016. [20] S.C. Woolley, P.N. Howard, “Automation, algorithms, and politics| political communication, computational propaganda, and autonomous agent – Introduction”, International Journal of Communication, vol. 10, 2016, pp. 4882–4890.",
year = "2019",
month = "5",
day = "26",
language = "English",
pages = "252--254",
booktitle = "Extensive and Intensive Models of Botnet Influence over Target Audience",
edition = "Atlantis Press",

}

Василькова, ВВ, Легостаева, НИ & Радушевский, ВБ 2019, Extensive and Intensive Models of Botnet Influence over Target Audience. в Extensive and Intensive Models of Botnet Influence over Target Audience . Atlantis Press ред., Paris, France, стр. 252-254.

Extensive and Intensive Models of Botnet Influence over Target Audience. / Василькова, Валерия Валентиновна; Легостаева, Наталья Игоревна; Радушевский, Владимир Борисович.

Extensive and Intensive Models of Botnet Influence over Target Audience . Atlantis Press . ред. Paris, France, 2019. стр. 252-254.

Результат исследований: Публикации в книгах, отчётах, сборниках, трудах конференцийстатья в сборникенаучнаярецензирование

TY - CHAP

T1 - Extensive and Intensive Models of Botnet Influence over Target Audience

AU - Василькова, Валерия Валентиновна

AU - Легостаева, Наталья Игоревна

AU - Радушевский, Владимир Борисович

N1 - [1] A. Bessi, E. Ferrara, “Social Bots Distort the 2016 US Presidential Election Online 8 Discussion”, First Monday, 2016, vol. 21(11). [2] Y. Boshmaf, I. Muslukhov, K. Beznosov, M. Ripeanu, “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. [3] R. Calo, “Robotics and the Lessons of Cyberlaw”, Cal. L. Rev., 2015, vol. 103(3). [4] E. Ferrara, O. Varol, C. Davis, F. Menczer, A. Flammini, “The rise of social bots”, Communications of the ACM, vol. 59(7), 2016, pp. 96–104. [5] A. Følstad, P.B. Brandtzæg, “Chatbots and the new world of HCI. Interactions”, vol. 24(4), July-August 2017, pp. 38-42. [6] M.C. Forelle, P.N. Howard, A. Monroy-Hernandez, S. Savage, “Political bots and the manipulation of public opinion in Venezuela”, Oxford, UK: Project on Computational Propaganda, 2015. [7] R. Gorwa, D. Guilbeault, “Unpacking the Social Media Bot: A Typology to Guide Research and Polic”,. Policy & Internet, 2018. [8] P.N. Howard, G. Bolsover, B. Kollanyi, S. Bradshaw, L.-M. Neudert, “Junk news and bots during the U.S. Election: What were Michigan voters sharing over Twitter?”, Working Papers & DataMemos. Oxford, UK: Project on Computational Propaganda, 2017. [9] P.N. Howard, S. Woolley, R. Calo, “Algorithms, bots, and political communication in the US 2016 election: The challenge of automated political communication for election law and administration”, Journal of Information Technology & Politics, vol. 15(2), 2018, pp. 81-93. [10] D. Murthy, A.B. Powell, R. Tinati, N. Anstead, L. Carr, S.J. Halford, M. Weal, “Automation, algorithms, and politics| Bots and political influence: A sociotechnical investigation of social network capital”, International Journal of Communication, vol. 10, 2016, pp. 4952–4971. [11] S. Nagaraja, A. Houmansadr, P. Piyawongwisal, V. Singh, P. Agarwal, N. Borisov, “Stegobot: a covert social network botnet”, in International Workshop on Information Hiding. Springer, Berlin, Heidelberg, 2011, pp. 299-313. [12] G. Neff, P. Nagy, “Automation, algorithms, and politics| talking to bots: symbiotic agency and the case of tay”, International Journal of Communication, vol. 10, 2016, pp. 4915–4931. [13] F. Schäfer, S. Evert, P. Heinrich, “Japan's 2014 General Election: Political Bots, Right-Wing Internet Activism, and Prime Minister Shinzō Abe's Hidden Nationalist Agenda”, Big data, vol. 5(4), 2017, pp. 294-309. [14] S. Shorey, P.N. Howard, “Automation, Algorithms, and Politics| Automation, Big Data and Politics: A Research Review”, International Journal of Communication, vol. 10, 2016, pp. 5032–5055. [15] S. Stieglitz, F. Brachten, B. Ross, A-K. Jung, “ Do Social Bots Dream of Electric Sheep? A Categorisation of Social Media Bot Accounts”, Australasian Conference on Information Systems. Hobart, Australia, 2017. [16] M. Tsvetkova, R. García-Gavilanes, L. Floridi, T. Yasseri, “Even good bots fight: The case of Wikipedia”, PLoS ONE 12(2): e0171774, 2017. [17] B. Waugh, M. Abdinpanah, O. Hashemi, S.A. Rahman, D.M. Cook, “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. [18] J.A. Williams, D.M. Miller, “Netizens Decide 2014? A Look at Party Campaigning Online. In Japan Decides”, 2nd ed. Palgrave Macmillan, London, 2016, pp 144-152. [19] S.C. Woolley, “Automating power: Social bot interference in global politics”, First Monday, vol. 21(4), 2016. [20] S.C. Woolley, P.N. Howard, “Automation, algorithms, and politics| political communication, computational propaganda, and autonomous agent – Introduction”, International Journal of Communication, vol. 10, 2016, pp. 4882–4890.

PY - 2019/5/26

Y1 - 2019/5/26

N2 - In the article, authors make an overview of existing approaches to typologization of bots and suggest their own approach for distinguishing botnets based on the influence of botnets over target audience. Using the logic of this approach, authors have performed a comparative analysis of two botnets found in the “VKontakte” social network, which revealed existence of two models of influence over target audience: extensive and intensive. Among the criteria for comparative analysis, botnets are characterized by “number of technological accounts in the botnet”, “intensity of publication activities”. Authors assume that the choice of one of these two models depends on thematic orientation of botnets, which involves different types of potential audiences.

AB - In the article, authors make an overview of existing approaches to typologization of bots and suggest their own approach for distinguishing botnets based on the influence of botnets over target audience. Using the logic of this approach, authors have performed a comparative analysis of two botnets found in the “VKontakte” social network, which revealed existence of two models of influence over target audience: extensive and intensive. Among the criteria for comparative analysis, botnets are characterized by “number of technological accounts in the botnet”, “intensity of publication activities”. Authors assume that the choice of one of these two models depends on thematic orientation of botnets, which involves different types of potential audiences.

KW - боты

KW - ботсети

KW - типология ботов

KW - методики выявления ботов

KW - экстенсивные и интенсивные модели

KW - bots

KW - botnets

KW - typology of bots

KW - botnet detection techniques

KW - intensive and extensive models

M3 - Article in an anthology

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EP - 254

BT - Extensive and Intensive Models of Botnet Influence over Target Audience

CY - Paris, France

ER -

Василькова ВВ, Легостаева НИ, Радушевский ВБ. Extensive and Intensive Models of Botnet Influence over Target Audience. В Extensive and Intensive Models of Botnet Influence over Target Audience . Atlantis Press ред. Paris, France. 2019. стр. 252-254