Chien-Hsiang Liao
Department of Information Management,
Fu Jen Catholic University, New Taipei City, Taiwan
Article published in
"Computers in Human Behavior" Volume 101, December 2019, Pages 457-465
Recently, big data and its applications have drawn the attention of academic researchers and business professionals. However, there are still a number of potential and useful values hidden in large-scale data. For instance, the large volumes of human activity data in social media might reflect people's consumption patterns and preferences. The aim of this study is to adopt social computing to explore valuable patterns or knowledge from social structures. This study develops five algorithms by integrating the notions of anticipatory computing and social network analysis, and also designs an application interface (API) which can be utilized in big data. These analytics can be applied to develop various applications in different contexts, e.g., marketing strategies in business or disease/symptom analysis in healthcare. This study contributes to social computing and discloses intelligent patterns in the social network.[Full article]
Keywords: Social computing, Anticipatory computing, Social network, Relational marketing, Decision making
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