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ThinkMind // HUSO 2016, The Second International Conference on Human and Social Analytics // View article huso_2016_3_10_70048


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

Authors:
Clayton J. Hutto

Keywords: human centered data science; human social analytics

Abstract:
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.

Pages: 48 to 54

Copyright: Copyright (c) IARIA, 2016

Publication date: November 13, 2016

Published in: conference

ISSN: 2519-8351

ISBN: 978-1-61208-519-7

Location: Barcelona, Spain

Dates: from November 13, 2016 to November 17, 2016

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