ANALYZING AND EXTRACTING SOCIALMINING TRENDS THROUGH WEB OPINION DEVELOPMENTS VIA DENSITY BASED CLUSTERING
Journal Title: International Journal of Advanced Research in Computer Engineering & Technology(IJARCET) - Year 2013, Vol 2, Issue 1
Abstract
The advancement of Web technologieslead to a large volume of Web opinions,which is available throughout on social media sites such as twitters,Facebook and LinkedIn. These technologies provide a platform for Internet users around the world to communicate with each other and express their various opinions. Analysis of developing Web opinions is potentially valuable for discovering ongoing topics of interests of the public such as current trends and crime detection. Unlike regular documents, Web opinions are short and sparse text messages with noisy content. Typical document clustering techniques with the goal of clustering all documents applied to Web opinions produce degradable performance. In this paper, we investigated the density-based clustering algorithm and proposed the scalable distance-based clustering technique for Web opinion clustering. This Web opinion clustering technique enables the identification of themes within discussions in web social networks and their development, as well as the interactions ofactive participants. We also developed interactive visualization tools, which make use of the identified topic clusters to display social network development, the network topology similarity between topics, and the similarity values between participants.
Authors and Affiliations
Jeswin Roy Dcouth , MohanRaj. T
Keywords
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