This link has been bookmarked by 126 people . It was first bookmarked on 12 Jul 2006, by Ray.
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Mike HENTREPRENEURSHIP EXAM
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empirical stochastic modeling
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This project was generously supported by our partners and collaborators at Nokia.
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20 Dec 11
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global pulse"Reality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling. "
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22 Jan 11
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21 Dec 10
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11 Dec 10
Giacomo BenincasaReality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.The original Reality Mining experiment is one of the largest mobile phone projects attempted in academia. Our research agenda takes advantage of the increasingly widespread use of mobile phones to provide insight into the dynamics of both individual and group behavior. By leveraging recent advances in machine learning we are building generative models that can be used to predict what a single user will do next, as well as model behavior of large organizations.
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07 Dec 10
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19 Nov 10
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17 Oct 10
Simon GianoutsosReality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout
research social mobile mit data visualization socialnetworks socialnetworking
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05 Aug 10
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22 Jul 10
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28 Apr 10
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Reality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.
The original Reality Mining experiment is one of the largest mobile phone projects attempted in academia. Our research agenda takes advantage of the increasingly widespread use of mobile phones to provide insight into the dynamics of both individual and group behavior. By leveraging recent advances in machine learning we are building generative models that can be used to predict what a single user will do next, as well as model behavior of large organizations.
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19 Apr 10
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18 Apr 10
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30 Jan 10
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09 Jan 10
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14 Dec 09
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08 Dec 09
Angus HongReality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout
research mobile datamining visualization ai privacy technology sns ubicomp soc
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01 Dec 09
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23 Nov 09
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30 Oct 09
Mark A.M. Kramer"Reality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling."
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01 Oct 09
Erhardt GraeffAmazing data sources and interesting look at sociology of digitized lives
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20 Sep 09
John Rodrigues"Reality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughou
datamining mobile statistics social research academic ai network analytics
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09 Sep 09
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05 Sep 09
Martin FilliauReality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.
social research mobile mining datamining mit networks technology
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01 Sep 09
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26 Aug 09
Carlos SantosMobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.
The original Reality Mining experiment is one of the largest mobile phone projects attempted in academia. Our research agenda takes advantage of the increasingly widespread use of mobile phones to provide insight into the dynamics of both individual and group behavior. By leveraging recent advances in machine learning we are building generative models that can be used to predict what a single user will do next, as well as model behavior of large organizations.RealityMining dataset MachineLearning mobile socialnetworkanalysis
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22 Jun 09
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24 Feb 09
Ricardo SatoReality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout
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13 Feb 09
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01 Feb 09
trevor harwoodReality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior.
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30 Nov 08
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16 Nov 08
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13 Oct 08
Lisa SpiroReality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.
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14 Aug 08
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07 Aug 08
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04 Aug 08
Christopher Arnold"Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling."
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12 Jul 08
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02 Jul 08
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22 Jun 08
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13 Jun 08
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Soledad Caballeromobile phone experiment that collected data from call logs, Bluetooth devices in proximity, cell tower IDs, application usage and phone status (such as charging and idle).
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03 Jun 08
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02 Jun 08
nmaisonneuveHow do social networks evolve over time?
research complexity datamining social_computing urban_computing place lab cmusp
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22 May 08
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12 Apr 08
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09 Apr 08
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28 Feb 08
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29 Jan 08
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Dante-Gabryell MonsonReality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout
MetaData ReferenceMaps Projects Arevoir Research SocialNetworks visualization Systems Anthropology art Communities Complexity Data Design Networks NetworkSociety Maps Mobile Swarm Organizational DataMining Psychology Academic Media for:mbauwens for:srose
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03 Jan 08
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29 Dec 07
Michel BauwensReality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout
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21 Dec 07
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Reality Mining defines the collection of machine-sensed environmental data pertaining to human social behavior. This new paradigm of data mining makes possible the modeling of conversation context, proximity sensing, and temporospatial location throughout large communities of individuals. Mobile phones (and similarly innocuous devices) are used for data collection, opening social network analysis to new methods of empirical stochastic modeling.
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26 Nov 07
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22 Nov 07
Adam CroweSpooky sh*t that makes me want to disappear into a lead-lined cave. DO NOT READ THIS!
* realitymining surveillance panopticon simulation privacy freedom liberty bluetooth proximity socialnetworking mapping datamining database crowds anthropology networks people ethnography psychology psychogeography research mobile location security smartm
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The Reality Mining experiment is one of the largest academic mobile phone projects in the US. Our research agenda takes advantage of the increasingly widespread use of mobile phones to provide insight into the dynamics of both individual and group behavior. By leveraging recent advances in machine learning we are building generative models that can be used to predict what a single user will do next, as well as model behavior of large organizations. We are currently capturing communication, proximity, location, and activity information from 100 subjects at MIT over the course of this academic year. To date, we have collected approximately 350,000 hours (~40 years) of continious data on human behavior. Such rich data on complex social systems have implications for a variety of fields. It is our hope that this research will help us explore research questions including: * How do incoming students' social networks evolve over time? * How entropic (predictable) are most people's lives? * Can the topology of a social network be inferred from only proximity data? * How can we change a group's interactions to promote better functioning?
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The Reality Mining experiment is one of the largest academic mobile phone projects in the US. Our research agenda takes advantage of the increasingly widespread use of mobile phones to provide insight into the dynamics of both individual and group behavior. By leveraging recent advances in machine learning we are building generative models that can be used to predict what a single user will do next, as well as model behavior of large organizations. We are currently capturing communication, proximity, location, and activity information from 100 subjects at MIT over the course of this academic year. To date, we have collected approximately 350,000 hours (~40 years) of continious data on human behavior. Such rich data on complex social systems have implications for a variety of fields. It is our hope that this research will help us explore research questions including: * How do incoming students' social networks evolve over time? * How entropic (predictable) are most people's lives? * Can the topology of a social network be inferred from only proximity data? * How can we change a group's interactions to promote better functioning?
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