Applied Social Network Analysis With R: Emerging Research and Opportunities

Applied Social Network Analysis With R: Emerging Research and Opportunities

Mehmet Gençer (Izmir University of Economics, Turkey)
Release Date: February, 2020|Copyright: © 2020 |Pages: 284
DOI: 10.4018/978-1-7998-1912-7
ISBN13: 9781799819127|ISBN10: 1799819124|EISBN13: 9781799819141|ISBN13 Softcover: 9781799819134
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Description & Coverage
Description:

Understanding the social relations within the fields of business and economics is vital for the promotion of success within a certain organization. Analytics and statistics have taken a prominent role in marketing and management practices as professionals are constantly searching for a competitive advantage. Converging these technological tools with traditional methods of business relations is a trending area of research.

Applied Social Network Analysis With R: Emerging Research and Opportunities is an essential reference source that materializes and analyzes the issue of structure in terms of its effects on human societies and the state of the individuals in these communities. Even though the theme of the book is business-oriented, an approach underlining and strengthening the ties of this field of study with social sciences for further development is adopted throughout. Therefore, the knowledge presented is valid for analyzing not only the organization of the business world but also for the organization of any given community. Featuring research on topics such as network visualization, graph theory, and micro-dynamics, this book is ideally designed for researchers, practitioners, business professionals, managers, programmers, academicians, and students seeking coverage on analyzing social and business networks using modern methods of statistics, programming, and data sets.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Business Networks
  • Data Sets
  • Evolutionary Algorithms
  • Graph Theory
  • Micro-Dynamics
  • Network Visualization
  • Non-Local Centrality
  • R Programming
  • Social Embeddedness
  • Social Media Analysis
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