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Social Evolution Dataset - Publications and Findings
Dong and colleagues [Dong et al., 2011] showed that subjects chose friends according to how often they see one another, and influence one another in participating in physical exercises, student activities, dietary behaviors, and others. They further proposed a stochastic process model to capture the co-evolution of social relationships and individual behavior with 12 events. They showed that such a stochastic process model could help researchers to interpolate between surveys with sensor data, and that it could potentially anonymize the "human behavior trails" through a resampling.
Dong and colleagues [Dong et al., 2012a] showed that it is possible to fit agent based models with the "data exhaust trails" of networked people by identifying agent based models as stochastic processes, through a case study that tells who infects whom in real-world social network.
Madan and colleagues were able to track stress, sadness, and flu by looking at how the subjects moved around, how much they talked to the others, and when they talked to the others [Madan et al., 2010a]. They were also able to explain the change in weight of a subject by the weight changes of his contacts on a weekly basis [Madan et al., 2010b].
Madan and colleagues inspected the political opinions and discussions of the subjects during the 2008 presidential election. They found that people tended to be close to those with the same political opinions during the presidential debates using Bluetooth scanning [Madan et al., 2011].
- [Dong et al., 2012b] Wen Dong, Katherine A. Heller, and Alex Pentland. Graph-Coupled HMMs for Modeling the Spread of Infection. In Proceedings of Uncertainty in Artificial Intelligence (UAI), pages 266-275, 2012.
- [Dong et al., 2012a] Wen Dong, Katherine A. Heller, and Alex Pentland. Modeling infection with multi-agent dynamics. In Proceedings of Social computing, Behavior-cultural modeling, and Prediction (SBP), pages 172-179, 2012. Best pape award.
- [Dong et al., 2011] Wen Dong, Bruno Lepri, and Alex Pentland. Modeling the co-evolution of behaviors and social relationships using mobile phone data. In Proceedings of the 10th International Conference on Mobile and Ubiquitous Multimedia (MUM), pages 134-143, 2011. Extended version in Tsinghua Science and Technology 2012, 17(2) 136-151
- [Madan et al., 2011] Anmol Madan, Katayoun Farrahi, Daniel Gatica-Perez, and Alex Pentland. Pervasive sensing to model political opinions in face-to-face networks. In Proceedings of the 9th International Conference on Pervasive Computing (Pervasive), pages 214-231, 2011.
- [Madan et al., 2010a] Anmol Madan, Manuel Cebrian, David Lazer, and Alex Pentland. Social sensing for epidemiological behavior change. In Proceedings of the 12th ACM international conference on ubiquitous computing (UbiComp), pages 291-300, 2010. Best paper runner-up.
- [Madan et al. 2010b] Anmol Madan, Sai T. Moturu, David Lazer, and Alex Pentland. Social sensing: obesity, unhealthy eating and exercise in face-to-face networks. In Proceedings of Wireless Health 2010 (WH), pages 104-110, 2010.
- Pentland A, Lazer D, Brewer D, Heibeck T., Using reality mining to improve public health and medicine. Stud Health Technol Inform. 2009;149:93-102.
- Anmol Madan and Alex Pentland. Modeling Diffusion Phenomena using Reality Mining. AAAI Spring Symposium, 2009, pp. 43-48.
- I Chronis, A Madan, AS Pentland. Socialcircuits: the art of using mobile phones for modeling personal interactions Proceedings of the ICMI-MLMI'09, 2009
- Alex Pentland. Reality Mining of Mobile Communications: Toward a New Deal on Data World Economic Forum Global Report on Information Technology, 2008-2009, pp.75-80