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dc.contributor.authorMadan, Anmol Prem Prakash
dc.contributor.authorFarrahi, Katayoun
dc.contributor.authorGatica-Perez, Daniel
dc.contributor.authorPentland, Alex Paul
dc.date.accessioned2011-09-15T21:37:28Z
dc.date.available2011-09-15T21:37:28Z
dc.date.issued2011-06
dc.identifier.isbn9783642217265
dc.identifier.isbn3642217265
dc.identifier.urihttp://hdl.handle.net/1721.1/65862
dc.description.abstractExposure 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 di erent 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 e ects have been measured. Automatically esti- mated exposure explains individual opinions on election day. Finally, we report statistically signi cant di erences in the daily activities of individ- uals that change political opinions versus those that do not, by modeling and discovering dominant activities using topic models. We nd people who decrease their interest in politics are routinely exposed (face-to-face) to friends with little or no interest in politics.en_US
dc.description.sponsorshipU.S. Army Research Laboratory (Cooperative Agreement No. W911NF-09-2-0053)en_US
dc.description.sponsorshipUnited States. Air Force Office of Scientific Research (Award No. FA9550-10-1-0122)en_US
dc.description.sponsorshipSwiss National Science Foundationen_US
dc.language.isoen_US
dc.publisherSpringeren_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/978-3-642-21726-5_14en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceMIT web domainen_US
dc.titlePervasive sensing to model political opinions in face-to-face networksen_US
dc.typeArticleen_US
dc.identifier.citationMadan, Anmol et al. “Pervasive Sensing to Model Political Opinions in Face-to-Face Networks.” Pervasive Computing. Ed. Kent Lyons, Jeffrey Hightower, & Elaine M. Huang. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. 214-231. Copyright © 2011, Springer Berlin / Heidelbergen_US
dc.contributor.departmentMassachusetts Institute of Technology. Engineering Systems Divisionen_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)en_US
dc.contributor.approverPentland, Alex Paul
dc.contributor.mitauthorMadan, Anmol Prem Prakash
dc.contributor.mitauthorPentland, Alex Paul
dc.relation.journalPervasive computing. (9th International Conference, 2011) (Lecture notes in computer science ; v. 6696)en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
dspace.orderedauthorsMadan, Anmol; Farrahi, Katayoun; Gatica-Perez, Daniel; Pentland, Alexen
dc.identifier.orcidhttps://orcid.org/0000-0002-8053-9983
mit.licenseOPEN_ACCESS_POLICYen_US


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