The research is aimed at investigating knowledge-based social informatics solutions. Socio-economic development relies on technology use in education and employment sectors. To explore such challenges, we examine the existing indicators of socio-economic development, such as gender equalities, employment, and education and population growth attribute dimensions. To understand them precisely, we analyse large-size human ecosystems and their data analytics. Social-informatics and -intelligence analysis are proposed with the design of logical and physical data schemas in diverse socio-economic contexts and their interoperability in varied geographies. We compute predictive models for different attribute dimensions, usable by technology developers and policy-makers. We interpret the data views of digital human ecosystems in the form of various graphs, tables, and polynomial regressions to envisage the influence of technology on societal collisions. The polynomial regressions suggest a strong positive relationship between different socio-economic attributes, cognizing the social intelligence and its knowledge management in Asia-Pacific contexts.
Nimmagadda, Shastri; Reiners, Torsten; Mani, Neel; and Namugenyi, Christine, "Social Informatics guided Social Intelligence Management and its Analysis in the Asia-Pacific Contexts" (2020). PACIS 2020 Proceedings. 221.
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