Sentiment and Mood Analysis of Weblogs Using POS Tagging Based Approach

The experimental work involves transforming the collected blog data into vector space representation, doing Parts of Speech Tagging to extract opinionated words and then applying semantic orientation approach based SO-PMI-IR algorithm for mining the sentiment and mood information contained in the blog text.

Abstract

This paper presents our experimental work on analysis of sentiments and mood from a large number of Weblogs (blog posts) on two interesting topics namely ‘Women’s Reservation in India’ and ‘Regionalism’. The experimental work involves transforming the collected blog data into vector space representation, doing Parts of Speech Tagging to extract opinionated words and then applying semantic orientation approach based SO-PMI-IR algorithm for mining the sentiment and mood information contained in the blog text. We obtained interesting results, which have been successfully evaluated for correctness through both manual tagging and by cross-validating the outcomes with other machine learning techniques. The results demonstrate that these analytical schemes can be successfully used for blog post analysis in addition to the review texts. The paper concludes with a short discussion of relevance of the work and its applied perspective.