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Implications of Data Density and Length of Collection Period for Population Estimations Using Social Media Data

  • Samuel Lee ToepkeEmail author
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 936)

Abstract

When programmatically utilizing public APIs provided by social media services, it is possible to attain a large volume of volunteered geographic information. Geospatially enabled data from Twitter, Instagram, Panaramio, etc. can be used to create high-resolution estimations of human movements over time, with volume of the data being of critical importance. This investigation extends previous work, showing the effects of artificial data removal, and generated error; though using over twice as much collected data, attained using an enterprise cloud solution, over a span of thirteen months instead of five.

Keywords

Media Enterprise systems Cloud Volunteered geographic data 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Private Engineering FirmWashington DCUSA

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