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The Silence of the Cantons: Estimating Villages Socioeconomic Status Through Mobile Phones Data
14 references·0 citing·40 second hop
The Silence of the Cantons: Estimating Villages Socioeconomic Status Through Mobile Phones Data (2018)The Silence of the Cantons: Estimating Vi…Understanding the bias of call detail records in human mobility research (2016)Understanding the bias of cal…Constructing spatiotemporal poverty indices from big data (2016)Constructing spatiotemporal p…Beyond the Baseline (2016)Beyond the BaselineMobile Phone Call Data as a Regional Socio-Economic Proxy Indicator (2015)Mobile Phone Call Data as a R…Poverty on the cheap (2014)Poverty on the cheapThe impact of biases in mobile phone ownership on estimates of human mobility (2013)The impact of biases in mobil…Human mobility characterization from cellular network data (2013)Human mobility characterizati…Characterizing social response to urban earthquakes using cell-phone network data (2013)Characterizing social respons…On the relationship between socio-economic factors and cell phone usage (2012)On the relationship between s…On the relation between socio-economic status and physical mobility (2012)On the relation between socio…Prediction of Socioeconomic Levels Using Cell Phone Records (2011)Prediction of Socioeconomic L…Prediction of socioeconomic levels using cell phone records (2011)Prediction of socioeconomic l…Network Diversity and Economic Development (2010)Network Diversity and Economi…Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis (2006)Mobile Landscapes: Using Loca…Understanding individual human mobility patterns (2008)Limits of Predictability in Human Mobility (2010)Big Data Integration (2013)Urban Sensing Using Mobile Phone Network Data: A Survey of Research (2014)On data processing required to derive mobility patterns from passively-generated mobile phone data (2017)A test of the technology acceptance model: the case of cellular telephone adoption (2005)M-PESA: Mobile Money for the “Unbanked” Turning Cellphones into 24-Hour Tellers in Kenya (2007)A new aspect on P2P online lending default prediction using meta-level phone usage data in China (2018)Computational socioeconomics (2019)Measuring objective and subjective well-being: dimensions and data sources (2020)The Strength of Weak Ties (1973)The Strength of Weak Ties: A Network Theory Revisited (1983)Structural Holes (1992)Digital Footprints: Opportunities and Challenges for Online Social Research (2014)European commitment to COP21 and the role of energy consumption, FDI, trade and economic complexity in sustaining economic growth (2020)Social capital I: measurement and associations with economic mobility (2022)Sources of Slow Growth in African Economies (1997)Social network activity and social well-being (2010)A universal model for mobility and migration patterns (2012)The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good (2017)Me++ (2003)Me++: The Cyborg Self and the Networked City (2003)Dynamic population mapping using mobile phone data (2014)A survey of results on mobile phone datasets analysis (2015)Human mobility: Models and applications (2018)Reality mining: sensing complex social systems (2005)Exploring the capacity of social media data for modelling travel behaviour: Opportunities and challenges (2016)Gender gaps in urban mobility (2020)A Computer Movie Simulating Urban Growth in the Detroit Region (1970)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)Editorial: human dynamics in the mobile and big data era (2016)Using Google Location History data to quantify fine-scale human mobility (2018)Future directions in human mobility science (2023)The Measurement of Multidimensional Poverty (2003)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Predicting poverty and wealth from mobile phone metadata (2015)Machine Learning at Central Banks (2017)Value creation for realising the sustainable development goals: Fostering organisational adoption of big data analytics (2020)Are we underestimating urban poverty? (2017)Combining disparate data sources for improved poverty prediction and mapping (2017)
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References

  • 2006Mobile Landscapes: Using Location Data from Cell Phones for Urban Analysis865 cited
  • 2010Network Diversity and Economic Development772 cited
  • 2013Human mobility characterization from cellular network data311 cited
  • 2013The impact of biases in mobile phone ownership on estimates of human mobility246 cited
  • 2016Understanding the bias of call detail records in human mobility research146 cited
  • 2011Prediction of Socioeconomic Levels Using Cell Phone Records108 cited
  • 2016Constructing spatiotemporal poverty indices from big data90 cited
  • 2011Prediction of socioeconomic levels using cell phone records89 cited
  • 2012On the relationship between socio-economic factors and cell phone usage85 cited
  • 2014Poverty on the cheap82 cited
  • 2015Mobile Phone Call Data as a Regional Socio-Economic Proxy Indicator55 cited
  • 2012On the relation between socio-economic status and physical mobility42 cited
  • 2013Characterizing social response to urban earthquakes using cell-phone network data34 cited
  • 2016Beyond the Baseline13 cited

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