Research Article
Opinion Mining from Weblogs and Its Relevance for Socio-political Research
@INPROCEEDINGS{10.1007/978-3-642-27308-7_14, author={Vivek Singh and Mousumi Mukherjee and Ghanshyam Mehta and Shekhar Garg and Nisha Tiwari}, title={Opinion Mining from Weblogs and Its Relevance for Socio-political Research}, proceedings={Advances in Computer Science and Information Technology. Computer Science and Engineering. Second International Conference, CCSIT 2012, Bangalore, India, January 2-4, 2012. Proceedings, Part II}, proceedings_a={CCSIT PATR II}, year={2012}, month={11}, keywords={Blogosphere Computational Sociology Opinion Mining Sentiment Analysis Social Computing}, doi={10.1007/978-3-642-27308-7_14} }- Vivek Singh
Mousumi Mukherjee
Ghanshyam Mehta
Shekhar Garg
Nisha Tiwari
Year: 2012
Opinion Mining from Weblogs and Its Relevance for Socio-political Research
CCSIT PATR II
Springer
DOI: 10.1007/978-3-642-27308-7_14
Abstract
This paper presents our experimental work on mining of opinions from a large number of blog posts and its relevance for socio-political research. The experimental work involves collecting blog data on three interesting topics, transforming the collected blog data into vector space representation, and then performing opinion mining using both a machine learning text classifier and an unsupervised semantic orientation approach. We implemented Naïve Bayes and SO-PMI-IR algorithms for opinion mining. We obtained interesting results, which have been evaluated for correctness and also cross-validated with the outcomes of multiple techniques employed. The paper concludes with a short discussion of the results and relevance of the experimental work.
