Extracting value and data analytic from social networks: Big data approach

Firman Arifin*, Mochamad Hariadi, Muhammad Anshari

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

The massive adoption of social networks and media have provided a means to extract value from the conversation taking place. Extracting value from social network enables organization to broaden their services beyond the usual practices, and thus provides a particular advantageous environment to achieve complex organization goals. The paper provides some of the empirical evidence about the potential impact of extracting value and data analytics from social networks using big data approach. Researchers have employed contents analysis for reviewing literatures in peer-reviewed journals and develop prototype for data analytics of users, topic, and time analytics. ASPRI is the prototype of the big data analytics. For this study, ASPRI focuses on social networks analytics, however the scope of ASPRI is extended to accommodate structured data sources like enterprise resources data and unstructured data sources like video and audio. Regardless of the limitations of the study, the model and prototype have a great support for the capabilities of social networks in generating value for organization in understanding pattern of their users. The findings provide initial ideas and recommendation for a future direction of big data analytic focusing on multi sources data.

Original languageEnglish
Pages (from-to)5286-5288
Number of pages3
JournalAdvanced Science Letters
Volume23
Issue number6
DOIs
Publication statusPublished - 2017

Keywords

  • Big data
  • Data analytics
  • Pervasive knowledge
  • Social networks
  • Value creation

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