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

Chien Hsiang Liao, Mu Yen Chen

研究成果: Article同行評審

4 引文 斯高帕斯(Scopus)

摘要

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.

原文English
頁(從 - 到)457-465
頁數9
期刊Computers in Human Behavior
101
DOIs
出版狀態Published - 2019 十二月

All Science Journal Classification (ASJC) codes

  • 藝術與人文(雜項)
  • 人機介面
  • 心理學(全部)

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