Web opinion mining for social networking sites

Bishas Kaur, Aarpit Saxena, Sanjay Singh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Web technologies provide a platform for Internet users around the world to communicate and express their opinions. Analysis of developing Web opinions is potentially valuable for discovering ongoing topics of interest like religion, politics and crime detection, understanding how topics evolve together with the underlying social interaction between participants, and identifying important participants who have great influence in various topics of discussions. In this paper, we investigate the density-based clustering algorithm and use the scalable distance-based clustering technique for Web opinion clustering which gives more reliable and accurate results. We have conducted experiments and benchmarked with the density-based algorithm to show that the new algorithm has better performance. This Web opinion clustering technique enables the identification of themes within discussions in Web social networks their development, as well as the interactions of active participants. With the help of interactive visualization tools, we make use of the identified topic clusters to display social network development, the net- work topology, similarity between topics, and the similarity values between participants. Using this we can successfully compare different threads on social networking sites, extract useful information from them and identify the underlying themes of discussions.

Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Computational Science, Engineering and Information, CCSEIT 2012
Pages598-605
Number of pages8
DOIs
Publication statusPublished - 12-12-2012
Event2nd International Conference on Computational Science, Engineering and Information, CCSEIT 2012 - Coimbatore, India
Duration: 26-10-201228-10-2012

Conference

Conference2nd International Conference on Computational Science, Engineering and Information, CCSEIT 2012
CountryIndia
CityCoimbatore
Period26-10-1228-10-12

Fingerprint

Crime
Clustering algorithms
Visualization
Topology
Internet
Experiments

All Science Journal Classification (ASJC) codes

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

Cite this

Kaur, B., Saxena, A., & Singh, S. (2012). Web opinion mining for social networking sites. In Proceedings of the 2nd International Conference on Computational Science, Engineering and Information, CCSEIT 2012 (pp. 598-605) https://doi.org/10.1145/2393216.2393316
Kaur, Bishas ; Saxena, Aarpit ; Singh, Sanjay. / Web opinion mining for social networking sites. Proceedings of the 2nd International Conference on Computational Science, Engineering and Information, CCSEIT 2012. 2012. pp. 598-605
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Kaur, B, Saxena, A & Singh, S 2012, Web opinion mining for social networking sites. in Proceedings of the 2nd International Conference on Computational Science, Engineering and Information, CCSEIT 2012. pp. 598-605, 2nd International Conference on Computational Science, Engineering and Information, CCSEIT 2012, Coimbatore, India, 26-10-12. https://doi.org/10.1145/2393216.2393316

Web opinion mining for social networking sites. / Kaur, Bishas; Saxena, Aarpit; Singh, Sanjay.

Proceedings of the 2nd International Conference on Computational Science, Engineering and Information, CCSEIT 2012. 2012. p. 598-605.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Kaur B, Saxena A, Singh S. Web opinion mining for social networking sites. In Proceedings of the 2nd International Conference on Computational Science, Engineering and Information, CCSEIT 2012. 2012. p. 598-605 https://doi.org/10.1145/2393216.2393316