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Inf. Syst."],"published-print":{"date-parts":[[2017,10,31]]},"abstract":"<jats:p>\n            Users with demographic profiles in social networks offer the potential to understand the social principles that underpin our highly connected world, from individuals, to groups, to societies. In this article, we harness the power of network and data sciences to model the interplay between user demographics and social behavior and further study to what extent users\u2019 demographic profiles can be inferred from their mobile communication patterns. By modeling over 7 million users and 1 billion mobile communication records, we find that during the active dating period (i.e., 18--35 years old), users are active in broadening social connections with males and females alike, while after reaching 35 years of age people tend to keep small, closed, and same-gender social circles. Further, we formalize the demographic prediction problem of inferring users\u2019 gender and age simultaneously. We propose a factor graph-based\n            <jats:italic>WhoAmI<\/jats:italic>\n            method to address the problem by leveraging not only the correlations between network features and users\u2019 gender\/age, but also the interrelations between gender and age. In addition, we identify a new problem\u2014coupled network demographic prediction across multiple mobile operators\u2014and present a coupled variant of the\n            <jats:italic>WhoAmI<\/jats:italic>\n            method to address its unique challenges. Our extensive experiments demonstrate the effectiveness, scalability, and applicability of the\n            <jats:italic>WhoAmI<\/jats:italic>\n            methods. Finally, our study finds a greater than 80% potential predictability for inferring users\u2019 gender from phone call behavior and 73% for users\u2019 age from text messaging interactions.\n          <\/jats:p>","DOI":"10.1145\/3057278","type":"journal-article","created":{"date-parts":[[2017,7,11]],"date-time":"2017-07-11T20:00:35Z","timestamp":1499803235000},"page":"1-33","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["User Modeling on Demographic Attributes in Big Mobile Social Networks"],"prefix":"10.1145","volume":"35","author":[{"given":"Yuxiao","family":"Dong","sequence":"first","affiliation":[{"name":"University of Notre Dame, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nitesh V.","family":"Chawla","sequence":"additional","affiliation":[{"name":"University of Notre Dame, IN, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jie","family":"Tang","sequence":"additional","affiliation":[{"name":"Tsinghua University, Beijing, P. 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