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Bots, Elections, and Social Media: A Brief Overview

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Disinformation, Misinformation, and Fake News in Social Media

Part of the book series: Lecture Notes in Social Networks ((LNSN))

Abstract

Bots, software-controlled accounts that operate on social media, have been used to manipulate and deceive. We studied the characteristics and activity of bots around major political events, including elections in various countries. In this chapter, we summarize our findings of bot operations in the context of the 2016 and 2018 US Presidential and Midterm elections and the 2017 French Presidential election.

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Notes

  1. 1.

    See Wikipedia: https://en.wikipedia.org/wiki/Russian_interference_in_the_2016_United_States_elections

  2. 2.

    Botometer: https://botometer.iuni.iu.edu/

  3. 3.

    BotSlayer: https://osome.iuni.iu.edu/tools/botslayer/

  4. 4.

    Bot Repository: https://botometer.iuni.iu.edu/bot-repository/

References

  1. Abokhodair, N., Yoo, D., McDonald, D.W.: Dissecting a social botnet: growth, content and influence in twitter. In: Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, pp. 839–851. ACM (2015)

    Google Scholar 

  2. Adamic, L.A., Glance, N.: The political blogosphere and the 2004 us election: divided they blog. In: 3rd International Workshop on Link Discovery, pp. 36–43. ACM (2005)

    Google Scholar 

  3. Alarifi, A., Alsaleh, M., Al-Salman, A.: Twitter turing test: identifying social machines. Inf. Sci. 372, 332–346 (2016)

    Article  Google Scholar 

  4. Allem, J.-P., Ferrara, E., Uppu, S.P., Cruz, T.B., Unger, J.B.: E-cigarette surveillance with social media data: social bots, emerging topics, and trends. JMIR Public Health Surveill. 3(4), e98 (2017)

    Article  Google Scholar 

  5. Aral, S., Walker, D.: Creating social contagion through viral product design: a randomized trial of peer influence in networks. Manag. Sci. 57(9), 1623–1639 (2011)

    Article  Google Scholar 

  6. Badawy, A., Ferrara, E., Lerman, K.: Analyzing the digital traces of political manipulation: the 2016 russian interference twitter campaign. In: Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2018 (2018)

    Google Scholar 

  7. Badawy, A., Lerman, K., Ferrara, E.: Who falls for online political manipulation? In: Companion Proceedings of the 2019 World Wide Web Conference, pp. 162–168 (2019)

    Google Scholar 

  8. Barberá, P., Wang, N., Bonneau, R., Jost, J.T., Nagler, J., Tucker, J., González-Bailón, S.: The critical periphery in the growth of social protests. PLoS One 10(11), e0143611 (2015)

    Article  Google Scholar 

  9. Bekafigo, M.A., McBride, A.: Who tweets about politics? political participation of twitter users during the 2011gubernatorial elections. Soc. Sci. Comput. Rev. 31(5), 625–643 (2013)

    Article  Google Scholar 

  10. Bessi, A., Ferrara, E.: Social bots distort the 2016 us presidential election online discussion. First Monday 21(11) (2016)

    Google Scholar 

  11. 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, pp. 93–102. ACM (2011)

    Google Scholar 

  12. Boyd, D., Crawford, K.: Critical questions for big data: provocations for a cultural, technological, and scholarly phenomenon. Inf. Commun. Soc. 15(5), 662–679 (2012)

    Article  Google Scholar 

  13. Carlisle, J.E., Patton, R.C.: Is social media changing how we understand political engagement? an analysis of facebook and the 2008 presidential election. Polit. Res. Q. 66(4), 883–895 (2013)

    Article  Google Scholar 

  14. Centola, D.: An experimental study of homophily in the adoption of health behavior. Science 334(6060), 1269–1272 (2011)

    Article  Google Scholar 

  15. Cha, M., Haddadi, H., Benevenuto, F., Gummadi, K.P.: Measuring user influence in twitter: the million follower fallacy. In: Fourth International AAAI Conference on Weblogs and Social Media (ICWSM 2010), pp. 10–17. AAAI Press (2010)

    Google Scholar 

  16. Chavoshi, N., Hamooni, H., Mueen, A.: Debot: twitter bot detection via warped correlation. In: ICDM, pp. 817–822 (2016)

    Google Scholar 

  17. Conover, M., Ratkiewicz, J., Francisco, M.R., Gonçalves, B., Menczer, F., Flammini, A.: Political polarization on twitter. ICWSM 133, 89–96 (2011)

    Google Scholar 

  18. Conover, M.D., Davis, C., Ferrara, E., McKelvey, K., Menczer, F., Flammini, A.: The geospatial characteristics of a social movement communication network. PLoS One 8(3), e55957 (2013)

    Article  Google Scholar 

  19. Conover, M.D., Ferrara, E., Menczer, F., Flammini, A.: The digital evolution of occupy wall street. PLoS One 8(5), e64679 (2013)

    Article  Google Scholar 

  20. Cresci, S., Di Pietro, R., Petrocchi, M., Spognardi, A., Tesconi, M.: The paradigm-shift of social spambots: evidence, theories, and tools for the arms race. In: Proceedings of the 26th International Conference on World Wide Web Companion, pp. 963–972. International World Wide Web Conferences Steering Committee (2017)

    Google Scholar 

  21. Davis, C.A., Varol, O., Ferrara, E., Flammini, A., Menczer, F.: Botornot: a system to evaluate social bots. In: WWW ’16 Companion Proceedings of the 25th International Conference Companion on World Wide Web, pp. 273–274. ACM (2016)

    Google Scholar 

  22. De Cristofaro, E., Kourtellis, N., Leontiadis, I., Stringhini, G., Zhou, S., et al.: Lobo: evaluation of generalization deficiencies in twitter bot classifiers. In: Proceedings of the 34th Annual Computer Security Applications Conference, pp. 137–146. ACM (2018)

    Google Scholar 

  23. DiGrazia, J., McKelvey, K., Bollen, J., Rojas, F.: More tweets, more votes: social media as a quantitative indicator of political behavior. PLoS One 8(11), e79449 (2013)

    Article  Google Scholar 

  24. Echeverria, J., Besel, C., Zhou, S.: Discovery of the twitter Bursty botnet. Data Science for Cyber-Security (2017)

    Google Scholar 

  25. Effing, R., Van Hillegersberg, J., Huibers, T.: Social media and political participation: are facebook, twitter and youtube democratizing our political systems? In International Conference on Electronic Participation, pp. 25–35. Springer (2011)

    Google Scholar 

  26. El-Khalili, S.: Social media as a government propaganda tool in post-revolutionary Egypt. First Monday 18(3) (2013)

    Google Scholar 

  27. Ferrara, E.: Manipulation and abuse on social media. ACM SIGWEB Newsletter (4) (2015)

    Google Scholar 

  28. Ferrara, E.: Disinformation and social bot operations in the run up to the 2017 french presidential election. First Monday 22(8) (2017)

    Google Scholar 

  29. Ferrara, E.: The history of digital spam. Commun. ACM 62(8), 2–91 (2019)

    Article  Google Scholar 

  30. Ferrara, E., Varol, O., Davis, C., Menczer, F., Flammini, A.: The rise of social bots. Commun. ACM 59(7), 96–104 (2016)

    Article  Google Scholar 

  31. Ferrara, E., Varol, O., Menczer, F., Flammini, A.: Detection of promoted social media campaigns. In: Tenth International AAAI Conference on Web and Social Media, pp. 563–566 (2016)

    Google Scholar 

  32. Ferrara, E., Yang, Z.: Measuring emotional contagion in social media. PLoS One 10(11), e0142390 (2015)

    Article  Google Scholar 

  33. Ferrara, E., Yang, Z.: Quantifying the effect of sentiment on information diffusion in social media. PeerJ Comput. Sci. 1, e26 (2015)

    Article  Google Scholar 

  34. Gao, H., Barbier, G., Goolsby, R.: Harnessing the crowdsourcing power of social media for disaster relief. IEEE Intell. Syst. 26(3), 10–14 (2011)

    Article  Google Scholar 

  35. Gao, H., Hu, J., Wilson, C., Li, Z., Chen, Y., Zhao, B.Y.: Detecting and characterizing social spam campaigns. In: Proceedings of the 10th ACM SIGCOMM Conference on Internet Measurement, pp. 35–47. ACM (2010)

    Google Scholar 

  36. Gilani, Z., Kochmar, E., Crowcroft, J.: Classification of twitter accounts into automated agents and human users. In: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, pp. 489–496. ACM (2017)

    Google Scholar 

  37. González-Bailón, S., Borge-Holthoefer, J., Moreno, Y.: Broadcasters and hidden influentials in online protest diffusion. Am. Behav. Sci. 57(7), 943–965 (2013)

    Article  Google Scholar 

  38. González-Bailón, S., Borge-Holthoefer, J., Rivero, A., Moreno, Y.: The dynamics of protest recruitment through an online network. Sci. Rep. 1, 197 (2011)

    Article  Google Scholar 

  39. Howard, P.N.: New Media Campaigns and the Managed Citizen. Cambridge University Press, Cambridge (2006)

    Google Scholar 

  40. Howard, P.N., Kollanyi, B.: Bots, #strongerin, and #brexit: computational propaganda during the uk-eu referendum. Available at SSRN 2798311 (2016)

    Google Scholar 

  41. Hwang, T., Pearce, I., Nanis, M.: Socialbots: voices from the fronts. Interactions 19(2), 38–45 (2012)

    Article  Google Scholar 

  42. Jagatic, T.N., Johnson, N.A., Jakobsson, M., Menczer, F.: Social phishing. Commun. ACM 50(10), 94–100 (2007)

    Article  Google Scholar 

  43. Jin, X., Lin, C., Luo, J., Han, J.: A data mining-based spam detection system for social media networks. Proceedings VLDB Endowment 4(12), 1458–1461 (2011)

    Article  Google Scholar 

  44. Kollanyi, B., Howard, P.N., Woolley, S.C.: Bots and automation over twitter during the first us presidential debate. Technical report, COMPROP Data Memo (2016)

    Google Scholar 

  45. Kramer, A.D., Guillory, J.E., Hancock, J.T.: Experimental evidence of massive-scale emotional contagion through social networks. Proc. Natl. Acad. Sci. 111(24), 8788–8790 (2014)

    Article  Google Scholar 

  46. Kudugunta, S., Ferrara, E.: Deep neural networks for bot detection. Inf. Sci. 467, 312–322 (2018)

    Article  Google Scholar 

  47. Kümpel, A.S., Karnowski, V., Keyling, T.: News sharing in social media: a review of current research on news sharing users, content, and networks. Soc. Media Soc. 1(2), 2056305115610141 (2015)

    Google Scholar 

  48. Kwak, H., Lee, C., Park, H., Moon, S.: What is twitter, a social network or a news media? In: Proceedings of the 19th International Conference on World Wide Web, pp. 591–600 (2010)

    Google Scholar 

  49. Latonero, M., Shklovski, I.: Emergency management, twitter, and social media evangelism. In: Using Social and Information Technologies for Disaster and Crisis Management, pp. 196–212. IGI Global, Hershey (2013)

    Google Scholar 

  50. Lazer, D., Pentland, A.S., Adamic, L., Aral, S., Barabasi, A.L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., et al.: Life in the network: the coming age of computational social science. Science (New York, NY) 323(5915), 721 (2009)

    Google Scholar 

  51. Lee, K., Caverlee, J., Webb, S.: The social honeypot project: protecting online communities from spammers. In: Proceedings of the 19th International Conference on World Wide Web, pp. 1139–1140. ACM (2010)

    Google Scholar 

  52. Lee, K., Caverlee, J., Webb, S.: Uncovering social spammers: social honeypots+ machine learning. In: Proceedings of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 435–442. ACM (2010)

    Google Scholar 

  53. Luceri, L., Deb, A., Badawy, A., Ferrara, E.: Red bots do it better: comparative analysis of social bot partisan behavior. In: Companion Proceedings of the 2019 World Wide Web Conference, pp. 1007–1012 (2019)

    Google Scholar 

  54. Luceri, L., Deb, A., Giordano, S., Ferrara, E.: Evolution of bot and human behavior during elections. First Monday 24(9) (2019)

    Google Scholar 

  55. Lutz, C., Hoffmann, C.P., Meckel, M.: Beyond just politics: a systematic literature review of online participation. First Monday 19(7) (2014)

    Google Scholar 

  56. Markines, B., Cattuto, C., Menczer, F.: Social spam detection. In: Proceedings of the 5th International Workshop on Adversarial Information Retrieval on the Web, pp. 41–48 (2009)

    Google Scholar 

  57. Messias, J., Schmidt, L., Oliveira, R., Benevenuto, F.: You followed my bot! transforming robots into influential users in twitter. First Monday 18(7) (2013)

    Google Scholar 

  58. Metaxas, P.T., Mustafaraj, E.: Social media and the elections. Science 338, 472–473 (2012)

    Article  Google Scholar 

  59. Minnich, A., Chavoshi, N., Koutra, D., Mueen, A.: Botwalk: efficient adaptive exploration of twitter bot networks. In: Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, pp. 467–474. ACM (2017)

    Google Scholar 

  60. Mønsted, B., Sapieżyński, P., Ferrara, E., Lehmann, S.: Evidence of complex contagion of information in social media: an experiment using twitter bots. PLos One 12(9), e0184148 (2017)

    Article  Google Scholar 

  61. Mukherjee, A., Liu, B., Glance, N.: Spotting fake reviewer groups in consumer reviews. In: Proceedings of the 21st International Conference on World Wide Web, pp. 191–200 (2012)

    Google Scholar 

  62. Mustafaraj, E., Metaxas, P.T.: From obscurity to prominence in minutes: political speech and real-time search (2010)

    Google Scholar 

  63. Pozzana, I., Ferrara, E.: Measuring bot and human behavioral dynamics. arXiv preprint arXiv:1802.04286 (2018)

    Google Scholar 

  64. Radford, A., Wu, J., Child, R., Luan, D., Amodei, D., Sutskever, I.: Language models are unsupervised multitask learners. OpenAI Blog 1(8) (2019)

    Google Scholar 

  65. Ratkiewicz, J., Conover, M., Meiss, M., Gonçalves, B., Flammini, A., Menczer, F.: Detecting and tracking political abuse in social media. ICWSM 11, 297–304 (2011)

    Google Scholar 

  66. Ratkiewicz, J., Conover, M., Meiss, M., Gonçalves, B., Patil, S., Flammini, A., Menczer, F.: Truthy: mapping the spread of astroturf in microblog streams. In: Proceedings of the 20th International Conference Companion on World Wide Web, pp. 249–252. ACM (2011)

    Google Scholar 

  67. Shao, C., Ciampaglia, G.L., Varol, O., Yang, K.-C., Flammini, A., Menczer, F.: The spread of low-credibility content by social bots. Nat. Commun. 9(1), 4787 (2018)

    Article  Google Scholar 

  68. Shorey, S., Howard, P.N.: Automation, algorithms, and politics— automation, big data and politics: a research review. Int. J. Commun. 10, 24 (2016)

    Google Scholar 

  69. Song, J., Lee, S., Kim, J.: Spam filtering in twitter using sender-receiver relationship. In: International Workshop on Recent Advances in Intrusion Detection, pp. 301–317 (2011)

    Google Scholar 

  70. Stella, M., Ferrara, E., De Domenico, M.: Bots increase exposure to negative and inflammatory content in online social systems. Proc. Natl. Acad. Sci. 115(49), 12435–12440 (2018)

    Article  Google Scholar 

  71. Stieglitz, S., Brachten, F., Ross, B., Jung, A.-K.: Do social bots dream of electric sheep? a categorisation of social media bot accounts. arXiv preprint arXiv:1710.04044 (2017)

    Google Scholar 

  72. Stringhini, G., Kruegel, C., Vigna, G.: Detecting spammers on social networks. In: Proceedings of the 26th Annual Computer Security Applications Conference, pp. 1–9. ACM (2010)

    Google Scholar 

  73. Stukal, D., Sanovich, S., Bonneau, R., Tucker, J.A.: Detecting bots on russian political twitter. Big Data 5(4), 310–324 (2017)

    Article  Google Scholar 

  74. Subrahmanian, V., Azaria, A., Durst, S., Kagan, V., Galstyan, A., Lerman, K., Zhu, L., Ferrara, E., Flammini, A., Menczer, F.: The darpa twitter bot challenge. Computer 49(6), 38–46 (2016)

    Article  Google Scholar 

  75. Sutton, J.N., Palen, L., Shklovski, I.: Backchannels on the Front Lines: Emergency Uses of Social Media in the 2007 Southern California Wildfires. University of Colorado, Boulder (2008)

    Google Scholar 

  76. Thelwall, M., Buckley, K., Paltoglou, G., Cai, D., Kappas, A.: Sentiment strength detection in short informal text. J. Am. Soc. Inf. Sci. Tech. 61(12), 2544–2558 (2010)

    Article  Google Scholar 

  77. Theocharis, Y., Lowe, W., van Deth, J.W., García-Albacete, G.: Using twitter to mobilize protest action: online mobilization patterns and action repertoires in the occupy wall street, indignados, and aganaktismenoi movements. Inf. Commun. Soc. 18(2), 202–220 (2015)

    Article  Google Scholar 

  78. Thomas, K., Grier, C., Song, D., Paxson, V.: Suspended accounts in retrospect: an analysis of twitter spam. In: Proceedings of the 2011 ACM SIGCOMM Conference on Internet Measurement Conference, pp. 243–258. ACM (2011)

    Google Scholar 

  79. Thomas, K., McCoy, D., Grier, C., Kolcz, A., Paxson, V.: Trafficking fraudulent accounts: the role of the underground market in twitter spam and abuse. In: Usenix Security, vol. 13, pp. 195–210 (2013)

    Google Scholar 

  80. Varol, O., Ferrara, E., Davis, C., Menczer, F., Flammini, A.: Online human-bot interactions: detection, estimation, and characterization. In: International AAAI Conference on Web and Social Media (2017)

    Google Scholar 

  81. Varol, O., Ferrara, E., Menczer, F., Flammini, A.: Early detection of promoted campaigns on social media. EPJ Data Sci. 6(1), 13 (2017)

    Article  Google Scholar 

  82. Varol, O., Ferrara, E., Ogan, C.L., Menczer, F., Flammini, A.: Evolution of online user behavior during a social upheaval. In: Proceedings 2014 ACM Conference on Web Science, pp. 81–90 (2014)

    Google Scholar 

  83. Vosoughi, S., Roy, D., Aral, S.: The spread of true and false news online. Science 359(6380), 1146–1151 (2018)

    Article  Google Scholar 

  84. Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications, vol. 8. Cambridge university press, New York (1994)

    Book  MATH  Google Scholar 

  85. Yang, C., Harkreader, R., Zhang, J., Shin, S., Gu, G.: Analyzing spammers’ social networks for fun and profit: a case study of cyber criminal ecosystem on twitter. In: Proceedings of the 21st International Conference on World Wide Web, pp. 71–80. ACM (2012)

    Google Scholar 

  86. Yang, K.-C., Varol, O., Davis, C.A., Ferrara, E., Flammini, A., Menczer, F.: Arming the public with artificial intelligence to counter social bots. Hum. Behav. Emerg. Technol. 1, e115 (2019)

    Article  Google Scholar 

  87. Yang, X., Chen, B.-C., Maity, M., Ferrara, E.: Social politics: agenda setting and political communication on social media. In: International Conference on Social Informatics, pp. 330–344. Springer (2016)

    Google Scholar 

  88. Yates, D., Paquette, S.: Emergency knowledge management and social media technologies: a case study of the 2010 haitian earthquake. Int. J. Inf. Manag. 31(1), 6–13 (2011)

    Article  Google Scholar 

  89. Yin, J., Lampert, A., Cameron, M., Robinson, B., Power, R.: Using social media to enhance emergency situation awareness. IEEE Intell. Syst. 27(6), 52–59 (2012)

    Article  Google Scholar 

  90. Zhang, X., Zhu, S., Liang, W.: Detecting spam and promoting campaigns in the twitter social network. In: Data Mining (ICDM), 2012 IEEE 12th International Conference on, pp. 1194–1199. IEEE (2012)

    Google Scholar 

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Acknowledgements

The author is grateful to his collaborators and coauthors on the topics covered in this paper, in particular Adam Badawy, Alessandro Bessi, Ashok Deb, and Luca Luceri, who contributed significantly to three papers widely discussed in this chapter [10, 53, 54].

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Ferrara, E. (2020). Bots, Elections, and Social Media: A Brief Overview. In: Shu, K., Wang, S., Lee, D., Liu, H. (eds) Disinformation, Misinformation, and Fake News in Social Media. Lecture Notes in Social Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-42699-6_6

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