Reality Mining

A brief introduction about Reality Mining

Transcript

1. Reality Mining
2. Virgílio Solano RA 180158 Universidade Estadual de Campinas Instituto de Computação Web e Web Semântica Prof. André Santanchè
3. Agenda ◎ Introduction ◎ What’s Reality Mining? ◎ Motivation ◎ Examples ◎ Research ◎ Challenges ◎ Conclusion ◎ Questions
5. “ A necessidade é a mãe da invenção. Armas, Germes e Aço Os destinos das sociedades Humanas. Jared Diamond
6. What’s Reality Mining? Computer Social Science Social Physics Social Network Patterns
7. “ We define reality mining as quantifying and modeling long-term human behavior and social interactions, by using mobile phones and wearable badges as sensors that capture realworld face-to-face interactions. Reality Mining and Personal Privacy Will Privacy Disappear when Social Sensors Learn Our Lives? - MIT Media Laboratory
9. Computer Science - Data Mining - Dynamic Networks - Behaviour Analysis - Machine Learning Methods - Statistical Analyses Reality Mining Social Science - Behaviour Analysis - Psychologic Social - Polytics and Economic Analysis - Health - Nature Analysis
10. Motivation Human Behavior Patterns Machine Learning Patterns Human Behavior Machine Learning
11. Examples Some examples using Reality Mining
12. Terrorist Tracking India
13. Predicting Congestion Traffic congestion predicted using mobile phone GPS data
14. Analyses the flow face-to-face and producvity Patterns of communication within departments of a bank
15. Reality Mining data from GPS Patterns of human movement in San Francisco Limited mixing among people with different behavior patterns
16. Health – Indentify depression Types speech and Variations : Pitch, variability of pitch and energy
17. Research Experiments
18. Modeling social diffusion using mobile phones Shows the pattern of proximity between people during one day
19. Modeling social diffusion using mobile phones Shows that different social relationships are associated with different patterns of proximity
20. Classifying spending behavior using socio-mobile data
21. Reality Mining and Social Network in nature
22. Many Researches - Efficient detection of contagious outbreaks in massive metropolitan encounter networks - The Social Amplifier – Reaction of Human Communities to Emergencies - Friends don’t Lie - Inferring Personality Traits from Social Network Structure - Limits of social mobilization - Incremental Learning with Accuracy Prediction of Social and Individual Properties from Mobile-Phone Data - The capacity to collect and analyze massive amounts of data unambiguously
23. Challenges Problems and solutions
24. Challenges - Security, Data ownership and privacy - Echo Chamber in network - Robust models of collaboration and data sharing between industry and the academy need to be developed that safeguard - How to developing technologies that protect privacy while preserving data essential for research? - How to integrate and approach Computer Science Scientists and Social Scientists? - Developer robust algorithms to process the big data around the world
25. Conclusion Some considerations
26. Conclusion - New way for understand to social mechanism and life - Improving methods to sharing private data and privacy policies - Advanced analysing big data around the world - Increase the efficiency and responsiveness of industries and governments. - Convenience for everything at today - Computational social science needs to be the work of teams of social and computer scientists. - Salvation or our destruction.
27. Thanks! Any questions? You can find me at: virgiliosolano.wordpress.com virgiliosolmag@gmail.com
28. References - T. Choudhury (2004) “Sensing and Modeling Human Networks.” Cambridge, MA USA, PhD Thesis, MIT Media Laboratory. - A. Pentland (2005) “Socially Aware Computation and Communication.” IEEE Computer,33-40. - F. Grippa, A. Zilli, R. Laubacher and P. Gloor (2006) “E-mail may not reflect the social network.” Proceedings of the North American Association for Computational Social and Organizational Science Conference. - A. Pentland (2006) “Automatic mapping and modeling of human networks.”, Physica A: Statistical Mechanics and its Applications. - A. Pentland (2006) “Life in the network: the coming age of computational social science”, http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2745217/, April; - A. Pentland (2006) “Automatic mapping and modeling of human networks.”, Physica A: Statistical Mechanics and its Applications. - S. Aral, E. Brynjolfssen and M.W. Van Alstyne (2007) “Productivity Effects of Information Diffusion in Networks,” MIT Center for Digital Business, paper 234 - L. Backstrom, C. Dwork, and J. Kleinberg (2007) “Wherefore Art Thou R3579X? Anonymized Social Networks, Hidden Patterns, and Structural Steganography.” WWW Conference. - M. Gonzalez, C. Hidalgo and A.-L. Barabási (2008) “Understanding Human Mobility Patterns.” Nature 453, pp 779-782. - B.N. Waber, D. Olguin Olguin, T. Kim and A. Pentland (2008) “Understanding Organizational Behavior with Wearable Sensing Technology.” Acadmey of Mangement Annual Conference. Anaheim, CA, USA. - B.N. Waber, D. Olguin Olguin, T. Kim and A. Pentland (2008) “Workplace Privacy.” EPIC Workplace Privacy Page. Electronic Privacy Information Center, 11 September 2008. Retrieved 14 July 2009 - A. Pentland. (2008) “Reality Mining of Mobile Communications: Toward a New Deal on Data”, http://hd.media.mit.edu/wef_globalit.pdf, April; - D. Lazer, D. Brewer, T. Heibeck and A. Pentland. (2009) “Improving Public Health and Medicine by use of Reality Mining”. http://hd.media.mit.edu/rwjf-reality-mining-whitepaper-0309.pdf, April.
29. References - N. Eagle and A. Pentland, (2009) “Reality Mining: Sensing Complex Social Systems”, Personal and Ubiquitous Computing, Vol 10, #4, 255-26. - N. Eagle and A. Pentland (2009) “Employee Monitoring: Is There Privacy in the Workplace?” Fact Sheet 7: Workplace Privacy. Privacy Rights Clearinghouse, April. - A. Madan, B. N. Waber, M. Ding, P. Kominers, and A. Pentland (2009) “Reality Mining and Personal Privacy”: Will Privacy Disappear when Social Sensors Learn Our Lives?, http://senseable.mit.edu/engagingdata/papers/ED_SIII_Reality_Mining_and_Personal_Privacy.pdf, April. - J. Krause, S. Krause, R. Arlinghaus, I. Psorakis, S. Roberts and C. Rutz (2013) “Reality mining of animal social systems”. http://www.igb-berlin.de/tl_files/data_igb/_aktuell_presse/_publikationen/KrauseEtAl_TREE_2013.pdf, April.