Optimizing Opinions with Stubborn Agents

References

• Acemoğlu D, Como G, Fagnani F, Ozdaglar A (2013) Opinion fluctuations and disagreement in social networks. Math. Oper. Res. 38(1):1–27.Link, Google Scholar
• Acemoglu D, Munther A, Dahleh IL, Ozdaglar A (2011) Bayesian learning in social networks. Rev. Econom. Stud. 78(4):1201–1236.Crossref, Google Scholar
• Alwin DF, Krosnick JA (1991) Aging, cohorts, and the stability of sociopolitical orientations over the life span. Amer. J. Sociol. 97(1):169–195.Crossref, Google Scholar
• Alwin DF, Cohen RL, Newcomb TM (1991) Political Attitudes over the Life Span: The Bennington Women after Fifty Years (University of Wisconsin Press, Madison, WI). Google Scholar
• Banerjee A (1992) A simple model of herd behavior. Quart. J. Econom. 107(3):797–817.Crossref, Google Scholar
• Banerjee A, Fudenberg D (2004) Word-of-mouth learning. Games Econom. Behav. 46(1):1–22.Crossref, Google Scholar
• Bikhchandani S, Hirshleifer D, Welch I (1992) A theory of fads, fashion, custom, and cultural change as informational cascades. J. Political Econom. 100(5):992–1026. Crossref, Google Scholar
• Byrnes N (2016) How the bot-y politic influenced this election. MIT Tech. Rev. (November 8), https://www.technologyreview.com/2016/11/08/69674/how-the-bot-y-politic-influenced-this-election/.Google Scholar
• Chatterjee S, Seneta E (1977) Toward consensus: Some convergence theorems on repeated averaging. J. Appl. Probab. 14(1):89–97.Crossref, Google Scholar
• Chen W, Wang Y, Yang S (2009) Efficient influence maximization in social networks. Proc. 15th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 199–208.Google Scholar
• Chen W, Wang C, Wang Y (2010) Scalable influence maximization for prevalent viral marketing in large-scale social networks. Proc. 16th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 1029–1038.Google Scholar
• Chinellato DD, Epstein IR, Braha D, Bar-Yam Y, de Aguiar MAM (2015) Dynamical response of networks under external perturbations: Exact results. J. Statist. Phys. 159(2):221–230.Crossref, Google Scholar
• Chollet F (2015) Keras. https://github.com/fchollet/keras.Google Scholar
• Clifford P, Sudbury A (1973) A model for spatial conflict. Biometrika 60(3):581–588.Crossref, Google Scholar
• Converse PE, Markus GB (1979) Plus ça change…: The new CPS election study panel. Amer. Political Sci. Rev. 73(1):32–49.Crossref, Google Scholar
• Cox JT, Griffeath D (1986) Diffusive clustering in the two dimensional voter model. Ann. Probab. 14(2):347–370.Crossref, Google Scholar
• DeGroot MH (1974) Reaching a consensus. J. Amer. Statist. Assoc. 69(345):118–121.Crossref, Google Scholar
• Fandos N, Shane S (2017) Senator berates Twitter over ‘inadequate’ inquiry into Russian meddling. New York Times (September 28), https://www.nytimes.com/2017/09/28/us/politics/twitter-russia-interference-2016-election-investigation.html.Google Scholar
• Ferrara E (2017) Disinformation and social bot operations in the run up to the 2017 French presidential election. First Monday 22(8).Google Scholar
• Galam S (2017) Geometric vulnerability of democratic institutions against lobbying: A sociophysics approach. Math. Models Methods Appl. Sci. 27(01):13–44.Crossref, Google Scholar
• Galam S, Jacobs F (2007) The role of inflexible minorities in the breaking of democratic opinion dynamics. Phys. A. 381:366–376.Crossref, Google Scholar
• Ghaderi J, Srikant R (2013) Opinion dynamics in social networks: A local interaction game with stubborn agents. Amer. Control Conf. (ACC) (IEEE, Piscataway, NJ), 1982–1987. Google Scholar
• Glenn ND (1980) Values, attitudes, and beliefs. Brim OG Jr, Kagan J, eds. Constancy and Change in Human Development (Harvard University Press, Cambridge, MA), 596–640.Google Scholar
• Gray L (1986) Duality for general attractive spin systems with applications in one dimension. Ann. Probab. 14(2):371–396. Crossref, Google Scholar
• Guilbeault D, Woolley S (2016) How Twitter bots are shaping the election. Atlantic (November 1), https://www.theatlantic.com/technology/archive/2016/11/election-bots/506072/.Google Scholar
• Hatano Y, Mesbahi M (2005) Agreement over random networks. IEEE Trans. Automatic Control 50(11):1867–1872.Crossref, Google Scholar
• Holley RA, Liggett TM (1975) Ergodic theorems for weakly interacting infinite systems and the voter model. Ann. Probab. 3(4):643–663. Crossref, Google Scholar
• Jackson MO (2010) Social and Economic Networks (Princeton University Press, Princeton, NJ).Crossref, Google Scholar
• Jadbabaie A, Lin J, Stephen Morse A (2003) Coordination of groups of mobile autonomous agents using nearest neighbor rules. IEEE Trans. Automatic Control 48(6):988–1001.Crossref, Google Scholar
• Jennings MK, Markus GB (1984) Partisan orientations over the long haul: Results from the three-wave political socialization panel study. Amer. Political Sci. Rev. 78(4):1000–1018.Crossref, Google Scholar
• Jennings MK, Niemi RG (2014) Generations and Politics: A Panel Study of Young Adults and Their Parents (Princeton University Press, Princeton, NJ).Google Scholar
• Kempe D, Kleinberg J, Tardos E (2003) Maximizing the spread of influence through a social network. Proc. Ninth ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 137–146.Google Scholar
• Kempe D, Kleinberg J, Tardos E (2005) Influential nodes in a diffusion model for social networks. Caires L, Italiano GF, Monteiro L, Palamidessi C, Yung M, eds. Automata, Languages and Programming (Springer, Berlin), 1127–1138.Crossref, Google Scholar
• Kim Y (2014) Convolutional neural networks for sentence classification. Proc. 2014 Conf. Empirical Methods Natl. Language Processing (EMNLP), Doha, Qatar (Association for Computational Linguistics), 1746–1751. https://aclanthology.org/D14-1181.Google Scholar
• Klausen J, Marks C, Zaman T (2018) Finding online extremists in social networks. Oper. Res. 66(4):957–976.Link, Google Scholar
• Krapivsky PL (1992) Kinetics of monomer-monomer surface catalytic reactions. Phys. Rev. A 45(2):1067.Crossref, Google Scholar
• Leskovec J, Krause A, Guestrin C, Faloutsos C, VanBriesen J, Glance N (2007) Cost-effective outbreak detection in networks. Proc. 13th ACM SIGKDD Internat. Conf. Knowledge Discovery Data Mining (ACM, New York), 420–429.Google Scholar
• Liggett TM (2012) Interacting Particle Systems (Springer, New York).Google Scholar
• Markus GB (1979) The political environment and the dynamics of public attitudes: A panel study. Amer. J. Political Sci. 23(2):338–359.Crossref, Google Scholar
• Martins ACR, Galam S (2013) Building up of individual inflexibility in opinion dynamics. Phys. Rev. E 87(4):042807.Crossref, Google Scholar
• Mason WA, Conrey FR, Smith ER (2007) Situating social influence processes: Dynamic, multidirectional flows of influence within social networks. Personality Soc. Psych. Rev. 11(3):279–300.Crossref, Google Scholar
• Mobilia M (2003) Does a single zealot affect an infinite group of voters? Phys. Rev. Lett. 91(2):028701.Crossref, Google Scholar
• Mobilia M, Petersen A, Redner S (2007) On the role of zealotry in the voter model. J. Statist. Mechanical Theory Experiment. 2007(08):P08029.Crossref, Google Scholar
• Moussaïd M, Kämmer JE, Analytis PP, Neth H (2013) Social influence and the collective dynamics of opinion formation. PLoS One 8(11):e78433.Crossref, Google Scholar
• Nemhauser GL, Wolsey LA, Fisher ML (1978) An analysis of approximations for maximizing submodular set functions—I. Math. Programming 14(1):265–294.Crossref, Google Scholar
• Olshevsky A, Tsitsiklis JN (2009) Convergence speed in distributed consensus and averaging. SIAM J. Control Optim. 48(1):33–55.Crossref, Google Scholar
• Parlapiano A, Lee JC (2018) The propaganda tools used by Russians to influence the 2016 election. New York Times (February 16), https://www.nytimes.com/interactive/2018/02/16/us/politics/russia-propaganda-election-2016.html.Google Scholar
• Price M (2018) Democrats urge Facebook and Twitter to probe Russian bots. CNET (January 23), https://www.cnet.com/news/facebook-and-twitter-asked-again-to-investigate-russian-bots/.Google Scholar
• Roberts BW, Walton KE, Viechtbauer W (2006) Patterns of mean-level change in personality traits across the life course: A meta-analysis of longitudinal studies. Psych. Bull. 132(1):1–25. Crossref, Google Scholar
• Sears DO (1975) Political socialization. Greenstein FI, Polsby NW, eds. Handbook of Political Science, vol. 2 (Addison-Wesley, Reading, MA), 93–153.Google Scholar
• Sears DO (1981) Life-stage effects on attitude change, especially among the elderly. Kiesler SB, Morgan JN, Oppenheimer VK, March JG, eds. Aging: Social Change (Academic Press, New York), 183–204.Google Scholar
• Sears DO (1983) The persistence of early political predispositions: The roles of attitude object and life stage. Rev. Personality Soc. Psych. 4(1):79–116.Google Scholar
• Sears DO, Funk CL (1999) Evidence of the long-term persistence of adults’ political predispositions. J. Politics 61(1):1–28.Crossref, Google Scholar
• Shane S (2017) The fake Americans Russia created to influence the election. New York Times (September 7), https://www.nytimes.com/2017/09/07/us/politics/russia-facebook-twitter-election.html.Google Scholar
• Shane S (2018) How unwitting Americans encountered Russian operatives online. New York Times (February 18), https://www.nytimes.com/2018/02/18/us/politics/russian-operatives-facebook-twitter.html.Google Scholar
• Sood V, Redner S (2005) Voter model on heterogeneous graphs. Phys. Rev. Lett. 94(17):178701. Crossref, Google Scholar
• Tahbaz-Salehi A, Jadbabaie A (2008) A necessary and sufficient condition for consensus over random networks. IEEE Trans. Automatic Control 53(3):791–795.Crossref, Google Scholar
• Tsitsiklis J (1984) Problems in decentralized decision making and computation. Technical report, Massachusetts Institute of Technology, Laboratory for Information and Decision Systems, Cambridge, MA.Google Scholar
• Tsitsiklis J, Bertsekas D, Athans M (1986) Distributed asynchronous deterministic and stochastic gradient optimization algorithms. IEEE Trans. Automatic Control 31(9):803–812.Crossref, Google Scholar
• Urbig D (2003) Attitude dynamics with limited verbalisation capabilities. J. Artificial Societies Soc. Simulation 6(1):2.Google Scholar
• Vassio L, Fagnani F, Frasca P, Ozdaglar A (2014) Message passing optimization of harmonic influence centrality. IEEE Trans. Control Network Systems 1(1):109–120.Crossref, Google Scholar
• Wu CW (2006) Synchronization and convergence of linear dynamics in random directed networks. IEEE Trans. Automatic Control 51(7):1207–1210.Crossref, Google Scholar
• Wu F, Huberman BA (2004) Social structure and opinion formation. Comput. Economics 0407002, University Library of Munich, Germany.Google Scholar
• Yildiz E, Ozdaglar A, Acemoglu D, Saberi A, Scaglione A (2013) Binary opinion dynamics with stubborn agents. ACM Trans. Econom. Comput. 1(4):19.Google Scholar