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Springer Verlag, Lecture Notes in Computer Science, p. 214-231

DOI: 10.1007/978-3-642-21726-5_14

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Pervasive Sensing to Model Political Opinions in Face-to-Face Networks

Proceedings article published in 2011 by Anmol Prem Prakash Madan, Katayoun Farrahi ORCID, Daniel Gatica-Perez, Alex Paul Pentland
This paper is available in a repository.
This paper is available in a repository.

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Abstract

Exposure and adoption of opinions in social networks are important questions in education, business, and government. We de- scribe 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 nd that self-reported political discussants have characteristic interaction patterns and can be predicted from sensor data. Mobile features can be used to estimate unique individ- ual exposure to dierent opinions, and help discover surprising patterns of dynamic homophily related to external political events, such as elec- tion debates and election day. To our knowledge, this is the rst time such dynamic homophily eects have been measured. Automatically esti- mated exposure explains individual opinions on election day. Finally, we report statistically signicant dierences