Social Network Analytics: Computational Research Methods And Techniques

Analyzing social network data is rapidly gaining interest in the scientific research community because of the importance of the information and insights that can be culled from the wealth of data inherent in the various aspects of the network. The analysis of social network data involves, basically, mapping and measuring the relationships and flows between people, groups, organizations, computers, URLs, and other connected information and knowledge entities. It is a difficult task due to availability of huge amounts of data along with very complex structures. Social Network Analytics focuses on various technical concepts and aspects of social network analysis. The book features the latest developments and findings in this emerging area of research. In addition, the book includes a variety of applications from several domains, such as scientific research, business, and industrial. The technical aspects of analysis are covered in detail, including visualizing and modeling, network theory, mathematical models, big data analytics of social networks, multidimensional scaling, and more! Examines a variety of data analytic techniques applied to social networks Discusses various methods of visualizing, modeling and tracking network patterns, organization, growth and change Covers the most recent research on social network analysis and includes applications to a number of domains

• | Author: Nilanjan Dey, Samarjeet Borah, Rosalina Babo, Amira Ashour
• | Publisher: Academic Press
• | Publication Date: Nov 23, 2018
• | Number of Pages: 267 pages
• | Language: English
• | Binding: Paperback/Computers
• | ISBN-10: 0128154586
• | ISBN-13: 9780128154588