Blending Quantitative, Qualitative, Geospatial, and Temporal Data: Progressing Towards the Next Generation of Human Social Analytics

摘要

Human social analytics in the next generation will need to embrace more multifaceted representations of human behavior with more complex models. Such models will need to integrate data of disparate forms, using disparate units of measure, collected from disparate sources, at disparate scales. Next generation social scientists will also face issues related to developing methods and tools to help facilitate the collection, processing, analyzing, and visualizing of such multifaceted social data. This paper illustrates these challenges by reporting on the development of a complex model of societal well-being (an inherently qualitative construct) which blends large scale quantitative, geospatial, and temporally referenced data of disparate forms, units, sources, and scales. We then demonstrate tools and methods intended to facilitate the progression towards next generational social analytics at large scales. We conclude by discussing several open questions with regards to social analytics, including those related to ethics and privacy concerns.