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Improving population estimation from mobile calls: A clustering approach
6 references·2 citing·35 second hop
Improving population estimation from mobile calls: A clustering approach (2016)Improving population estimation from mobi…City users' classification with mobile phone data (2015)City users' classification wi…Dynamic population mapping using mobile phone data (2014)Dynamic population mapping us…Where to go from here? Mobility prediction from instantaneous information (2013)Where to go from here? Mobili…Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones (2010)Using Mobile Positioning Data…Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome (2010)Real-Time Urban Monitoring Us…Mobile Landscapes: Graz in Real Time (2007)Mobile Landscapes: Graz in Re…Recognizing Residents and Tourists with Retail Data Using Shopping Profiles (2018)Recognizing Residents and Tou…Scalable and flexible clustering solutions for mobile phone-based population indicators (2017)Scalable and flexible cluster…Smart mobs: the next social revolution (2003)Smart Mobs: The Next Social Revolution (2003)Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Uncovering individual and collective human dynamics from mobile phone records (2008)New Approaches to Human Mobility: Using Mobile Phones for Demographic Research (2012)Discovering urban activity patterns in cell phone data (2015)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)Scripts, plans, goals, and understanding : an inquiry into human knowledge structures. By Roger C. Schank and Robert P. Abelson. Hillsdale, NJ: Lawrence Erlbaum Associates, 1977. Pp. 248. (1978)The New Mobilities Paradigm (2006)Beyond Space (As We Knew It): Toward Temporally Integrated Geographies of Segregation, Health, and Accessibility (2013)Predicting poverty and wealth from mobile phone metadata (2015)Social Media and the City: Rethinking Urban Socio-Spatial Inequality Using User-Generated Geographic Information (2015)Understanding individual human mobility patterns (2008)Computational Social Science (2009)Limits of Predictability in Human Mobility (2010)A survey of results on mobile phone datasets analysis (2015)Human development report 2015: work for human development (2015)OPERATIONAL PARAMETERS AFFECTING THE USE OF ANONYMOUS CELL PHONE TRACKING FOR GENERATING TRAFFIC INFORMATION (2003)Cellular Census: Explorations in Urban Data Collection (2007)Digital Footprinting: Uncovering Tourists with User-Generated Content (2008)Understanding individual mobility patterns from urban sensing data: A mobile phone trace example (2012)A literature survey on smart cities (2015)Friendship and mobility (2011)A Generative Model of Urban Activities from Cellular Data (2017)An exploration of the interaction between urban human activities and daily traffic conditions: A case study of Toronto, Canada (2018)Algorithms at Work: The New Contested Terrain of Control (2019)Social Event Detection in Massive Mobile Phone Data Using Probabilistic Location Inference (2011)Human mobility modeling at metropolitan scales (2012)Big Data Research in Italy: A Perspective (2016)Discovering and Understanding City Events with Big Data: The Case of Rome (2017)A Multi-City Urban Population Mobility Study Using Mobile Phone Traffic Data (2018)The relationship between place attachment and landscape values: Toward mapping place attachment (2007)MANUAL OF POLITICALECONOMY (2013)Geo-located Twitter as proxy for global mobility patterns (2014)Human migration: the big data perspective (2020)
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References

  • 2014Dynamic population mapping using mobile phone data929 cited
  • 2010Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome632 cited
  • 2010Using Mobile Positioning Data to Model Locations Meaningful to Users of Mobile Phones418 cited
  • 2007Mobile Landscapes: Graz in Real Time94 cited
  • 2013Where to go from here? Mobility prediction from instantaneous information48 cited
  • 2015City users' classification with mobile phone data32 cited

Cited by

  • 2017Scalable and flexible clustering solutions for mobile phone-based population indicators7 cited
  • 2018Recognizing Residents and Tourists with Retail Data Using Shopping Profiles7 cited

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