Home location inference from sparse and noisy data: models and applications

Ashbrook, D., Starner, T., 2003. Using GPS to learn significant locations and predict movement across multiple users. Pers. Ubiq. Comput., 7(5):275–286. http://dx.doi.org/10.1007/s00779-003-0240-0

Backstrom, L., Sun, E., Marlow, C., 2010. Find me if you can: improving geographical prediction with social and spatial proximity. Proc. 19th Int. Conf. on World Wide Web, p.61–70. http://dx.doi.org/10.1145/1772690.1772698

Cheng, Z., Caverlee, J., Lee, K., 2010. You are where you tweet: a content-based approach to geo-locating twitter users. Proc. 19th ACM Int. Conf. on Information and Knowledge Management, p.759–768. http://dx.doi.org/10.1145/1871437.1871535

Cheng, Z., Caverlee, J., Lee, K., et al., 2011. Exploring millions of footprints in location sharing services. Proc. 5th Int. AAAI Conf. on Weblogs and Social Media, p.81–88.

Cho, E., Myers, S.A., Leskovec, J., 2011. Friendship and mobility: user movement in location-based social networks. Proc. 17th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, p.1082–1090. http://dx.doi.org/10.1145/2020408.2020579

Cranshaw, J., Toch, E., Hong, J., et al., 2010. Bridging the gap between physical location and online social networks. Proc. 12th ACM Int. Conf. on Ubiquitous Computing, p.119–128. http://dx.doi.org/10.1145/1864349.1864380

Culotta, A., 2010. Towards detecting influenza epidemics by analyzing Twitter messages. Proc. 1st Workshop on Social Media Analytics, p.115–122. http://dx.doi.org/10.1145/1964858.1964874

Hoh, B., Gruteser, M., Xiong, H., et al., 2006. Enhancing security and privacy in traffic-monitoring systems. IEEE Perv. Comput., 5(4):38–46. http://dx.doi.org/10.1109/MPRV.2006.69

Krumm, J., 2007. Inference attacks on location tracks. Proc. 5th Int. Conf. on Pervasive Computing, p.127–143. http://dx.doi.org/10.1007/978-3-540-72037-9_8

Krumm, J., Rouhana, D., 2013. Placer: semantic place labels from diary data. Proc. ACM Int. Joint Conf. on Pervasive and Ubiquitous Computing, p.163–172. http://dx.doi.org/10.1145/2493432.2493504

Lin, M., Hsu, W., Lee, Z., 2012. Predictability of individuals’ mobility with high-resolution positioning data. Proc. ACM Conf. on Ubiquitous Computing, p.381–390. http://dx.doi.org/10.1145/2370216.2370274

Mahmud, J., Nichols, J., Drews, C., 2012. Where is this tweet from? Inferring home locations of Twitter users. Proc. 6th Int. AAAI Conf. on Weblogs and Social Media, p.511–514.

Paul, M.J., Dredze, M., 2011. A Model for Mining Public Health Topics from Twitter. Technical Report, Johns Hopkins University, USA.

Pontes, T., Magno, G., Vasconcelos, M., et al., 2012a. Beware of what you share: inferring home location in social networks. Proc. IEEE 12th Int. Conf. on Data Mining Workshops, p.571–578. http://dx.doi.org/10.1109/ICDMW.2012.106

Pontes, T., Vasconcelos, M., Almeida, J., et al., 2012b. We know where you live: privacy characterization of Foursquare behavior. Proc. ACM Conf. on Ubiquitous Computing, p.898–905. http://dx.doi.org/10.1145/2370216.2370419

Sadilek, A., Krumm, J., 2012. Far out: predicting long-term human mobility. Proc. 26th AAAI Conf. on Artificial Intelligence, p.814–820.

Sadilek, A., Kautz, H., 2013. Modeling the impact of lifestyle on health at scale. Proc. 6th ACM Int. Conf. on Web Search and Data Mining, p.637–646. http://dx.doi.org/10.1145/2433396.2433476

Sadilek, A., Kautz, H., Silenzio, V., 2012. Modeling spread of disease from social interactions. Proc. 6th Int. AAAI Conf. on Weblogs and Social Media.

Sapolsky, R. M., 2004. Social status and health in humans and other animals. Ann. Rev. Anthropol., 33:393–418.

Scellato, S., Noulas, A., Lambiotte, R., et al., 2011a. Sociospatial properties of online location-based social networks. Proc. 5th Int. AAAI Conf. on Weblogs and Social Media, p.329–336.

Scellato, S., Noulas, A., Mascolo, C., 2011b. Exploiting place features in link prediction on location-based social networks. Proc. 17th ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, p.1046–1054. http://dx.doi.org/10.1145/2020408.2020575

Smith, G., Wieser, R., Goulding, J., et al., 2014. A refined limit on the predictability of human mobility. Proc. IEEE Int. Conf. on Pervasive Computing and Communications, p.88–94. http://dx.doi.org/10.1109/PerCom.2014.6813948

Song, C., Qu, Z., Blumm, N., et al., 2010. Limits of predictability in human mobility. Science, 327(5968):1018–1021. http://dx.doi.org/10.1126/science.1177170

Winkleby, M.A., Jatulis, D.E., Frank, E., et al., 1992. Socioeconomic status and health: how education, income, and occupation contribute to risk factors for cardiovascular disease. Am. J. Public Health, 82(6):816–820. http://dx.doi.org/10.2105/AJPH.82.6.816

Xing, W., Ghorbani, A., 2004. Weighted pagerank algorithm. Proc. 2nd Annual Conf. on Communication Networks and Services Research, p.305–314. http://dx.doi.org/10.1109/DNSR.2004.1344743