Abstract
Exposure and adoption of opinions in social networks are important questions in education, business, and government. We describe a novel application of pervasive computing based on using mobile phone sensors to measure and model the face-to-face interactions and subsequent opinion changes amongst undergraduates, during the 2008 US presidential election campaign. We find that self-reported political discussants have characteristic interaction patterns and can be predicted from sensor data. Mobile features can be used to estimate unique individual exposure to different opinions, and help discover surprising patterns of dynamic homophily related to external political events, such as election debates and election day. To our knowledge, this is the first time such dynamic homophily effects have been measured. Automatically estimated exposure explains individual opinions on election day. Finally, we report statistically significant differences in the daily activities of individuals that change political opinions versus those that do not, by modeling and discovering dominant activities using topic models. We find people who decrease their interest in politics are routinely exposed (face-to-face) to friends with little or no interest in politics.
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References
Abdelzaher, T., Anokwa, Y., Boda, P., Burke, J., Estrin, D., Guibas, L., Kansal, A., Madden, S., Reich, J.: Mobiscopes for human spaces. IEEE Pervasive Computing - Mobile and Ubiquitous Systems 6(2) (2007)
Adamic, L., Glance, N.: The political blogosphere and the 2004 US election: divided they blog. In: Proc. of the 3rd Intl. Workshop on Link Discovery (2005)
Agarwal, N., Liu, H.: Modeling and Data Mining in Blogosphere, vol. 1. Morgan & Claypool Publishers, San Francisco (2009)
Avancha, S., Baxi, A., Kotz, D.: Privacy in mobile technology for personal healthcare. Submitted to ACM Computing Surveys (2009)
Bernard, H.R., Killworth, P., Kronenfeld, D., Sailer, L.: The Problem of Informant Accuracy: The Validity of Retrospective Data. Annual Reviews in Anthropology (1984)
Blei, D.M., Ng, A.Y., Jordan, M.I., Lafferty, J.: Latent dirichlet allocation. JMLR 3 (2003)
Boyd, D., Ellison, N.: Social network sites: Definition, history, and scholarship. Journal of Computer Mediated Communication 13(1), 210 (2007)
Brewer, D., Webster, C.: Forgetting of friends and its effects on measuring friendship networks. Social Networks 21(4), 361–373 (2000)
Burt, R.: Social contagion and innovation: Cohesion versus structural equivalence. American Journal of Sociology (1987)
Choudhury, T.: Sensing and Modeling Human Networks. PhD thesis, M.I.T (2003)
Choudhury, T.: Characterizing social networks using the sociometer. Association of Computational Social and Organizational Science (2004)
Choudhury, T., Basu, S.: Modeling Conversational Dynamics as a Mixed Memory Markov Process. In: NIPS (2004)
Bishop, C.: Pattern Recognition and Machine Learning. Springer, Heidelberg (2006)
Currarini, S., Jackson, M., Pin, P.: An Economic Model of Friendship: Homophily, Minorities, and Segregation. Econometrica 77(4), 1003–1045 (2009)
Eagle, N., Macy, M., Claxton, R.: Network Diversity and Economic Development. Science 328(5981), 1029–1031 (2010)
Eagle, N., Pentland, A., Lazer, D.: Inferring Social Network Structure Using Mobile Phone Data. PNAS 106(36), 15274–15278 (2009)
Miluzzo, E., et al.: Darwin Phones: The Evolution of Sensing and Inference on Mobile Phones. In: Mobisys (2010)
Farrahi, K., Gatica-Perez, D.: What did you do today? discovering daily routines from large-scale mobile data. ACM MM (2008)
Farrahi, K., Gatica-Perez, D.: Probabilistic mining of socio-geographic routines from mobile phone data. IEEE J-STSP 4(4), 746–755 (2010)
Freund, Y., Schapire, R.E.: A short introduction to boosting. Japonese Society for Artificial Intelligence 5, 771–780 (1999)
Friedkin, N.E.: A Structural Theory of Social Influence. Cambridge University Press, Cambridge (1998)
Gonzalez, M., Hidalgo, C., Barabasi, A.-L.: Understanding Individual Human Mobility Patterns. Nature 453, 779–782 (2008)
Granovetter, M.: Threshold models of collective behavior. American Journal of Sociology 83, 1420–1443 (1978)
Guo, F., Hanneke, S., Fu, W., Xing, E.P.: Recovering temporally rewiring networks: A model-based approach. In: ICML (2007)
Huckfeldt, R., Sprague, J.: Discussant Effects on Vote Choice: Intimacy, Structure and Interdependence. The Journal of Politics 53, 122–158 (1991)
Hunter, D.R., Handcock, M.S.: Inference in curved exponential family models for networks. Journal of Computational and Graphical Statistics 15, 565–583 (2006)
Huynh, T., Fritz, M., Schiele, B.: Discovery of activity patterns using topic models. In: UbiComp, Seoul, Korea, pp. 10–19 (2008)
Intentionally Blank. Intentionally blank
Kempe, D., Kleinberg, J., Tardos, E.: Maximizing the Spread of Influence in a Social Network. In: KDD 2003, Washington DC (2003)
Laibowitz, M., Gips, J., Aylward, R., Pentland, A., Paradiso, J.: A sensor network for social dynamics. In: IPSN, p. 491 (2006)
Lazarsfeld, P., Merton, R.K.: Friendship as a Social Process: A Substantive and Methodological Analysis. Freedom and Control in Modern Society (1954)
Lazer, D., Rubineau, B., Katz, N., Chetkovich, C., Neblo, M.A.: Networks and political attitudes: Structure, influence, and co-evolution. Working paper series (September 2008)
Leskovec, J., Backstrom, L., Kleinberg, J.: Meme-tracking and the Dynamics of the News Cycle. In: ACM SIGKDD (2009)
Liu, H., Salerno, J., Young, M.: Social Computing, Behavioral Modeling and Prediction. Springer, Heidelberg (2008)
Madan, A., Pentland, A.: Vibephones: Socially aware mobile phones. In: ISWC (2006)
Madan, A., Pentland, A.: Modeling Social Diffusion Phenomena Using Reality Mining. In: AAAI Spring Symposium on Human Behavior Modeling (2009)
Mccallum, A., Corrada-emmanuel, A., Wang, X.: The author-recipient-topic model for topic and role discovery in social networks: Experiments with enron and academic email. Technical report (2004)
McPherson, M., Smith-Lovin, L., Cook, J.M.: Birds of a Feather: Homophily in Social Networks. Annual Review of Sociology 27, 415–444 (2001)
Moturu, S.: Quantifying the Trustworthiness of Social Media Content: Content Analysis for the Social Web. Lambert Academic Publishing (2010)
Nallapati, R., Cohen, W.: Link-plsa-lda: A new unsupervised model for topics and influence in blogs. In: ICWSM (2008)
Olguin Olguin, D., Gloor, P., Pentland, A.: Wearable sensors for pervasive healthcare management. PCT Healthcare (2009)
Olguin Olguin, D., Waber, B., Kim, T., Mohan, A., Ara, K., Pentland, A.: Sensible organizations: Technology and methodology for automatically measuring organizational behavior. IEEE Transactions on Systems, Man, and Cybernetics-B (2009)
Pentland, A.: Socially aware computation and communication. In: ICMI (2005)
Richardson, M., Domingas, P.: Markob logic networks. Machine Learning (2006)
Robins, G., Snijders, T., Wang, P., Handcock, M., Pattison, P.: Recent developments in exponential random graph (p*) models for social networks. Social Networks 29(2), 192–215 (2007)
Roy, D., Patel, R., DeCamp, P., Kubat, R., Fleischman, M., Roy, B., Mavridis, N., Tellex, S., Salata, A., Guinness, J., Levit, M., Gorniak, P.: The human speechome project. In: Vogt, P., Sugita, Y., Tuci, E., Nehaniv, C.L. (eds.) EELC 2006. LNCS (LNAI), vol. 4211, pp. 192–196. Springer, Heidelberg (2006)
Steyvers, M., Smyth, P., Rosen-Zvi, M., Groffiths, T.: Probabilistic author-topic models for information discovery. In: ACM SIGKDD, pp. 306–315 (2004)
Wang, F., Carley, K., Zeng, D., Mao, W.: Social computing: From social informatics to social intelligence. IEEE Intelligent Systems, 79–83 (2007)
Wang, X., Mohanty, N., Mccallum, A.: Group and topic discovery from relations and text. In: ACM SIGKDD (Workshop on Link Discovery) (2005)
Wyatt, D., Choudhury, T., Bilmes, J.: Discovering Long Range Properties of Social Networks with Multi-Valued Time-Inhomogeneous Models. In: AAAI (2010)
Yano, T., Cohen, W.W., Smith, N.A.: Predicting response to political blog posts with topic models. In: NAACL 2009, pp. 477–485 (2009)
Zeng, D., Wang, F., Carley, K.: Guest Editors’ Introduction: Social Computing. IEEE Intelligent Systems, 20–22 (2007)
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Madan, A., Farrahi, K., Gatica-Perez, D., Pentland, A.(. (2011). Pervasive Sensing to Model Political Opinions in Face-to-Face Networks. In: Lyons, K., Hightower, J., Huang, E.M. (eds) Pervasive Computing. Pervasive 2011. Lecture Notes in Computer Science, vol 6696. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21726-5_14
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DOI: https://doi.org/10.1007/978-3-642-21726-5_14
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