Indonesian Music Fans Group Identification using Social Network Analysis in Kaskus Forum
Indonesian Music Fans Group Identification using Social Network Analysis in Kaskus Forum
Author : IMMANUEL MATTHIAS PANDAPOTAN; ANDRY ALAMSYAH; MARISA W. PARYASTO Published on : ICoICT 2015 (The 3rd International Conference of Information and Communication Technology)
Abstract
Abstract??? Online conversation can provide insights and patterns that are not easily visible, especially when many users involved in the conversation, thus increase the complexity and the conversation size. For music Industry, understanding the current music trends increase their ability to take an important business decision, thus leads to the success to conquer the market. Kaskus, the biggest online forum in Indonesia is a common media for millions Indonesian to discuss about many things, including their music preference. By mining the forum, we offer new insight about the interaction pattern among the users and identification of dominant music fans groups or topics in the conversations. We model the conversations using Social Network Analysis and implement community detection algorithm to identify group identification. There are two reasons on why the music industry should adopt data mining methods; it is considerably faster with almost real time and it is a cheaper alternative to conventional practice using surveys or questionnaires.
