Download PDF by Bruno Gonçalves, Nicola Perra: Social Phenomena: From Data Analysis to Models

By Bruno Gonçalves, Nicola Perra

ISBN-10: 3319140108

ISBN-13: 9783319140100

ISBN-10: 3319140116

ISBN-13: 9783319140117

This publication specializes in the recent chances and techniques to social modeling at the moment being made attainable via an extraordinary number of datasets generated via our interactions with sleek applied sciences. This sector has witnessed a veritable explosion of task over the past few years, yielding many attention-grabbing and worthy effects. Our target is to supply an outline of the state-of-the-art during this region of study, merging an incredibly heterogeneous array of datasets and types. Social Phenomena: From info research to Models is split into components. half I offers with modeling social habit below basic stipulations: How we are living, shuttle, collaborate and have interaction with one another in our day-by-day lives. half II offers with societal habit less than remarkable stipulations: Protests, armed insurgencies, terrorist assaults, and reactions to infectious illnesses. This booklet deals an outline of 1 of the main fertile rising fields bringing jointly practitioners from medical groups as diversified as social sciences, physics and desktop technology. we are hoping not to purely offer an unifying framework to appreciate and signify social phenomena, but additionally to assist foster the discussion among researchers engaged on related difficulties from diversified fields and perspectives.

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5 times over the course of a week. The distribution of time between encounters reveals strong periodicity, with passengers riding the same bus to work in the morning riding the same home, or riding the same bus at the same time each morning. This finding illustrates the idiosyncrasies of human mobility. Not only we visit a few places very during the day, but we also do so at the same times and by the same routes. Amazingly, though both of these results suggest that our unicity should be low, the previous work shows us that this is not the case.

ACM SIGMOBILE Mobile Computing and Communications Review, 16(3), 33–44. id=2412101. 17. González, M. , Hidalgo, C. , & Barabási, A. L. (2008). Understanding individual human mobility patterns. Nature, 453(7196), 779–782. 18. -L. (2010, September). Modelling the scaling properties of human mobility. Nature Physics, 6(10), 818–823 19. -L. (2010) Limits of predictability in human mobility. Science, 327(5968), 1018–1021. 20. , & Geisel, T. (2006). The scaling laws of human travel. Nature, 439, 462–465.

44. Herrera, J. , Work, D. , & Bayen, A. M. (2010). Evaluation of traffic data obtained via GPS-enabled mobile phones: The mobile century field experiment. Transportation Research Part C: Emerging Technologies, 18, 568–583. 45. Jariyasunant, J. (2012). Improving traveler information and collecting behavior data with smartphones. PhD thesis. 46. -X. (2015). Predictability of road traffic and congestion in urban areas. PLoS One, 10(4), e0121825. 0121825. 0121825. 47. , & González, M. C. (2014, January).

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Social Phenomena: From Data Analysis to Models by Bruno Gonçalves, Nicola Perra

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