Abstract
Spatial analysis refers to a set of techniques applied to the spatial expression of human behavior that echoes the rift between quantitative and economic geography. Despite its reliance on a statistical framework, spatial analysis has contended with methodological challenges that internet research scholars are increasingly negotiating, including the multidimensionality of the object of study, the interdisciplinary nature of the methodological approaches, and the strong dependence on computers for data collection and analysis. Together with traditional, often governmental sources of geographic information, internet-powered devices are generating a wealth of location-rich information ordinarily referred to as “geoweb.” The availability of such user-generated sources of spatial data, coupled with the rapid development of spatial analysis computing platforms, provides avenues for quantitative research on unprecedented scales and contributes to bringing these two areas of scholarship into closer contact with one another. The R environment for statistical computing offers a robust and unified platform where spatial and internet researchers alike can rely on a multitude of packages for spatial analysis and statistical computing. Researchers can use this computational resource to perform data analysis of streams of social media data with geographic references and/or coordinates that can be mapped to specific locations. This wealth of data allows researchers to ask meaningful geographical, sociological, and political research questions associated with the development of the internet that until now could only be evaluated more limitedly due to scanty data. This chapter aims to familiarize internet researchers with spatial analysis and to provide a soft learning curve to scholars unfamiliar with the R environment for statistical computing. To this end, an overview of methods, tools, and the literature dedicated to spatial analysis of internet-generated data is presented. The chapter also reviews seminal literature in the area, describes the core components of the R environment for spatial analysis, and provides an up-to-date overview of the possibilities spatial analysis scholarship offers to internet researchers.
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Bastos, M.T. (2020). Spatial Analysis Meets Internet Research. In: Hunsinger, J., Allen, M., Klastrup, L. (eds) Second International Handbook of Internet Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-1555-1_2
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