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L. Phillips, C. Dowling, K. Shaffer, and N. Hodas, and S. Volkova, “Using social media to predict the future: a systematic literature review,” arXiv: 1706.06134 (2017). D. A. Gubanov and A. G. Chkhartishvili, “A conceptual approach to online social networks analysis,” Autom. Remote Control 76, 1455–1462 (2015). M. Kosinski, D. Stillwell, and T. Graepel, “Private traits and attributes are predictable from digital records of human behavior,” Proc. Natl. Acad. Sci. U. S. A.110, 5802–5805 (2013). H. Schoen, D. Gayo-Avello, P. Takis Metaxas, E. Mustafaraj, M. Strohmaier, and P. Gloor, “The power of prediction with social media,” Internet Res. 23, 528–543 (2013). R. I. Dunbar, V. Arnaboldi, M. Conti, and A. Passarella, “The structure of online social networks mirrors those in the offline world,” Social Networks 43, 39–47 (2015). A. V. Proskurnikov and R. Tempo, “A tutorial on modeling and analysis of dynamic social networks. Part I,” Ann. Rev. Control (2018). A. A. Belolipetskii and I. V. Kozitsin, “Dynamic variant of mathematical model of collective behavior,” J. Comput. Syst. Sci. Int. 56, 385–396 (2017). I. V. Kozitsin, “Generalization of Krasnoshchekov’s model for the case of a decomposable matrix of social interactions,” Math. Models Comput. Simul. 10, 398–406 (2018). I. V. Kozitsin and A. A. Belolipetskii, “Opinion convergence in the Krasnoshchekov model,” J. Math. Sociol., 1–18 (2018). P. S. Krasnoshchekov, “The simplest mathematical model of behaviour. Psychology of conformism,” Mat. Model. 10 (7), 76–92 (1998). A. V. Proskurnikov and R. Tempo, “A tutorial on modeling and analysis of dynamic social networks. Part II,” Ann. Rev. Control (2018). E. D. Kornilina and A. P. Petrov, “Dynamic model of proximity of positions of social network users,” Math. Models Comput. Simul. 5, 213–219 (2013). P. Barberá, “How social media reduces mass political polarization. Evidence from Germany, Spain, and the US,” Job Market Paper (New York Univ., 2014), Vol. 46. P. Barberá, “Birds of the same feather tweet together: Bayesian ideal point estimation using Twitter data,” Polit. Anal. 23 (1), 76–91 (2015). R. Cohen and D. Ruths, “Classifying political orientation on Twitter: it’s not easy!,” in Proceedings of the International AAAI Conference on Weblogs and Social Media ICWSM,2013. A. P. Mikhailov, V. A. Shvedovskii, A. I. Maslov, and V. F. Kovalev, “The generalized model of choice behaviour and its application to ethno-political conflicts,” Mat. Model. 15 (8), 39–56 (2003). A. Tumasjan, T. O. Sprenger, P. G. Sandner, and I. M. Welpe, “Predicting elections with twitter: what 140 characters reveal about political sentiment,” in Proceedings of the 4th International AAAI Conference on Weblogs and Social Media ICWSM,2010. A. Boutet, H. Kim, and E. Yoneki, “What’s in Twitter, I know what parties are popular and who you are supporting now!,” Social Network Anal. Mining 3, 1379–1391 (2013). https://doi.org/10.7910/DVN/AKXXUI P. Flach, Machine Learning: The Art and Science of Algorithms that Make Sense of Data (Cambridge Univ. Press, Cambridge, 2012). D. Frey, “Recent research on selective exposure to information,” in Advances in Experimental Social Psychology (Academic, New York, 1986), Vol. 19, pp. 41–80. A. Chkhartishvili and I. Kozitsin, “Binary separation index for echo chamber effect measuring,” in Proceedings of the 2018 11th International Conference on Management of Large-Scale System Development (IEEE, 2018), pp. 1–4. K. Garimella, G. de Francisci Morales, A. Gionis, and M. Mathioudakis, “Political discourse on social media: echo chambers, gatekeepers, and the price of bipartisanship,” in Proceedings of the 2018 World Wide Web Conference (Int. World Wide Web Conf. Steering Committee, 2018), pp. 913–922. V. Viugin, Mathematical Foundations of Machine Learning and Forecasting (Litres, Moscow, 2017) [in Russian]. L. Weng, A. Flammini, A. Vespignani, and F. Menczer, “Competition among memes in a world with limited attention,” Sci. Rep. 2, 335 (2012). I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning (MIT Press, Boston, MA, 2016). C. Castellano, D. Vilone, and A. Vespignani, “Incomplete ordering of the voter model on small-world networks,” Europhys. Lett. 63, 153 (2003). V. Amelkin, P. Bogdanov, and A. K. Singh, “A distance measure for the analysis of polar opinion dynamics in social networks,” in Proceedings of the 33rd IEEE International Conference on Data Engineering ICDE,2017 (IEEE, 2017), pp. 159–162. A. P. Mikhailov, A. P. Petrov, N. A. Marevtseva, and I. V. Tretiakova, “Development of a model of information dissemination in society,” Math. Models Comput. Simul. 6, 535–541 (2014). A. P. Petrov, A. I. Maslov, and N. A. Tsaplin, “Modeling position selection by individuals during information warfare in society,” Math. Models Comput. Simul. 8, 401–408 (2016). A. P. Petrov and O. G. Proncheva, “Modeling propaganda battle: decision-making, homophily, and echo chambers,” in Proceedings of the Conference on Artificial Intelligence and Natural Language AINL 2018, Ed. by D. Ustalov, A. Filchenkov, L. Pivovarova, and J. Žižka, Vol. 930 of Communications in Computer and Information Science (Springer, Cham, 2018), pp. 197–209. A. P. Mikhailov, A. P. Petrov, G. B. Pronchev, and O. G. Proncheva, “Modeling a decrease in public attention to a past one-time political event,” Dokl. Math. 97, 247–249 (2018). A. P. Mikhailov and N. A. Marevtseva, “Models of information warfare,” Math. Models Comput. Simul. 4, 251–259 (2012).