Building social computing system in big data: From the perspective of social network analysis

Chien Hsiang Liao, Mu Yen Chen

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

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.

Original languageEnglish
Pages (from-to)457-465
Number of pages9
JournalComputers in Human Behavior
Volume101
DOIs
Publication statusPublished - 2019 Dec

All Science Journal Classification (ASJC) codes

  • Arts and Humanities (miscellaneous)
  • Human-Computer Interaction
  • Psychology(all)

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