Publication Type : Conference Proceedings
Publisher : 2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS), IEEE,
Source : 2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS), IEEE, Bengaluru, India (2016)
Url : https://ieeexplore.ieee.org/abstract/document/7779440
Keywords : betweenness, closeness, Companies, degree, digital age, eigen factor, Eigen vector, Electronic publishing, Encyclopedias, Facebook, Google Plus, Graph theory, graphs, Internet, Internet access, LinkedIn, measurement, network measures, network over social medium, network theory (graphs), Shape, social media network analysis, social media network visualization, Social networking (online), US politics
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Center : Center for Computational Engineering and Networking
Department : Computer Science
Verified : Yes
Year : 2016
Abstract : People seek for ways to communicate with others by connecting, networking and promoting with one another. Before, they used handshakes, word-of-mouth communications, letters, and phones. Now, they form a network over social medium. social networking has taken a new shape and momentum in this digital age with internet access and faster connectivity. Today's relationships are being developed on LinkedIn, Google Plus, and Facebook. These social networks can be drawn as a graph and analyzed for various network measures. From these measures, the most prominent people, their relationship and their influence on other persons in the network can be observed. Similarly, graphs can be used as prototypes to illustrate many types of relations and processes in chemical, physical, biological, and information systems. Many real time scenarios can be depicted by graphs. In this paper, a dataset comprising of books about US politics have been represented as a network and analyzed for their importance based on the metrics such as betweenness, eigen vector, degree, and closeness.
Cite this Research Publication : A. Malathi and Radha D., “Analysis and visualization of social media networks”, 2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS). IEEE, Bengaluru, India, 2016.