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Novel Approach for Online Forum Hotspot Detection

Faran Kazi, Shraddha Joshi, Sahista Machchhar, Krupa Mandaviya


Social network, online forums, blogs and various sites where people can hold conversation in the form of messages, is recently become a more valuable resource for mining in various fields like customer relationship management, public opinion tracking and other text mining entities. The knowledge obtained from these public forums is extremely valuable for marketing research companies. This paper also include information of various tools available for crawling data from online forums, sites or blogs. In first part emotional polarity for extracted text is obtained using python script. In second part combined approach using EM (Expectation Maximization) clustering and SVM classification algorithm is applied to detect weather given forum is hotspot or non-hotspot for given time window. This novel approach gives better result than previous approaches to detect hotspot forums. Among them EM gives better result instead of K-means Clustering Technique.


SVM (Support Vector Machine); EM (Expectation Maximization); Sentiment Analysis; Hotspot Detection; K-Means.

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T. Preethi, K. Nirmala Devi and V.Murali Bhaskaran, “A semantic enhanced approach for online hotspot forums detection”, In Proc. IEEE Recent Trends In Information Technology (ICRTIT), pp. 497-501, April 2012.

Li. Nan and Wu. Desheng Dash, "Using text mining and sentiment analysis for online forums hotspot detection and forecast", Decision Support Systems vol. 48, no.2, pp. 354-368, 2010.

G. Vinodhini and R. M. Chandrasekaran, "Sentiment analysis and opinion mining: a survey" International Journal vol.2, no.6, 2012.

T. M.Jothi and K.Thirumoorthy, “A Survey on Web Forum Crawling Techniques”, IJIRSET, pp. 1708-1714, 2014.

M. M. Mostafa, ”More than words: Social networks text mining for consumer brand sentiments”, Expert Systems with Applications, vol.40, no.10, pp.4241-4251, 2013.

X. Bai, ”Predicting consumer sentiments from online text”, Decision Support Systems, vol.50, no.4, pp. 732-742, 2011.

K. Nirmala Devi and V. Murali Bhaskarn, “Online Forums Hotspot Prediction Based on Sentiment Analysis", Journal of Computer Science vol.8, no.8, 2012.

K. Xu, S. S.Liao, J.Li and Y.Song, “Mining comparative opinions from customer reviews for Competitive Intelligence”, Decision support systems, vol.50, no.4, pp.743-754, 2011.

Olston, Christopher, and Marc Najork, "Web crawling" Foundations and Trends in Information Retrieval vol.4, no.3, pp.175-246, 2010.

Romero, Cristóbal, et al, "Predicting students' final performance from participation in on-line discussion forums", Computers & Education vol.68, pp. 458-472, 2013.

Liu, Hong and Xiaojun Li, "Internet public opinion hotspot detection research based on k-means algorithm", Advances in Swarm Intelligence, Springer, pp.594-602, 2010.

Asmi, Amna and Tanko Ishaya, "Negation Identification and Calculation in Sentiment Analysis", The Second International Conference on Advances in Information Mining and Management, 2012.

H. Liu, “Internet public opinion hotspot detection and analysis based on Kmeans and SVM algorithm”, In Proc. IEEE Information Science and Management Engineering (ISME),Vol. 1, pp. 257-261, 2010.

J. Han and M. Kamber, Data Mining: Concepts and Techniques, 2nd ed., Morgan Kaufmann Publisher, March 2006, ISBN 1-55860-901-6.

Vaghasiya, Priyanka D., and Sahista Machchhar. "Attribute Selection Methods with Classification Techniques in Educational Data Mining to Predict Student’s Performance: A Survey." Data Mining and Knowledge Engineering 7.1 , 2015.


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