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A process framework for big data research: social network analysis using design science

In: Handbook of Big Data Research Methods

Author

Listed:
  • Denis Dennehy
  • Samrat Gupta
  • John Oredo

Abstract

Managing and harnessing big data is increasingly being reported as an approach to generate business value, optimize decision-making, and achieve competitive advantage. There is strong evidence that research on big data has gained significant attention from both the academic community and analytics community. To date, research has largely focused on the technical aspects of big data and its applications in specific contexts, but with limited attention given to the underlying process. Yet, it is well accepted that understanding the processes required to leverage big data is a critical factor to realize the claimed benefits of big data. We address this knowledge deficit by designing a process framework to guide novice users to effectively apply social network analysis and improve the outputs of big data research projects. The framework is the artifact that emerged after applying the principles of design science research. The artifact was validated by a social network analysis of credit networks in India.

Suggested Citation

  • Denis Dennehy & Samrat Gupta & John Oredo, 2023. "A process framework for big data research: social network analysis using design science," Chapters, in: Shahriar Akter & Samuel Fosso Wamba (ed.), Handbook of Big Data Research Methods, chapter 14, pages 214-232, Edward Elgar Publishing.
  • Handle: RePEc:elg:eechap:20820_14
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