Social network visualization for interest in music

Abstract

In this paper, we addressed in social network visualization for people's interest in music. This visualization system designed for interest in music on social networks provides several capabilities: (A) visualization for friends who share the same interest in music, (B) to group people who share the same interest in music into categories, and (C) to recommend songs function for an increase in the common interest in music. These capabilities provide some essential capabilities for social networking analysis. Take the following for example: general users chat with others through instant messaging on social networks. Or perhaps, they would rather start up a discussion with other users. However, discussions of this kind that share similar interests can allow users to get to know others and improve interpersonal relationships. Afterwards, they can know their friends more about what they like and what dislike. In this dissertation, the research fellows need to handle the text information gathered from Plurk (the world-famous social network) to carry out regularization. We make use of the data mining method to analyze the information on the subject of music interest. We classify various types of songs. They also substitute these keywords called different degree of preference into the iSpreadRank algorithm to give different degree of preference. In our experience, this visualization system plays an essential rule in the analysis on social network.