Affiliation:
1. Aligarh Muslim University, India
Abstract
A social network can be defined as a complex graph, which is a collection of nodes connected via edges. Nodes represent individual actors or people in the network, whereas edges define relationships among those actors. Most popular social networks are Facebook, Twitter, and Google+. To analyze these social networks, one needs specialized tools for analysis. This chapter presents a comparative study of such tools based on the general graph aspects as well as the social network mining aspects. While considering the general graph aspects, this chapter presents a comparative study of four social network analysis tools—NetworkX, Gephi, Pajek, and IGraph—based on the platform, execution time, graph types, algorithm complexity, input file format, and graph features. On the basis of the social network mining aspects, the chapter provides a comparative study on five specialized tools—Weka, NetMiner 4, RapidMiner, KNIME, and R—with respect to the supported mining tasks, main functionality, acceptable input formats, output formats, and platform used.
Reference28 articles.
1. Akhtar, Javed, & Sengar. (2013). Analysis of High Degree Nodes in a Social Network. International Journal of Electronics, Communication and Computer Engineering, 4(3).
2. Analysis of Facebook Social Network;N.Akhtar;IEEE International Conference on Computational Intelligence and Computer Networks (CICN)
3. Automatic Summarization. (n.d.). In Wikipedia. Retrieved from https://en.wikipedia.org/wiki/Automatic_summarization
4. Business Application of Social Network Analysis (BASNA). (2013). Retrieved from www.basna.in
5. Carrington, P. J., & Scott, J. (2011). Introduction. In The Sage Handbook of Social Network Analysis. SAGE. Retrieved from http://www.facebook.com/notes/facebook/500millionstories/409753352130
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