Finding Opinionated Blogs Using Statistical Classifiers and Lexical Features

Authors

  • Feifan Liu The University of Texas at Dallas
  • Bin Li The University of Texas at Dallas
  • Yang Liu The University of Texas at Dallas

Keywords:

Sentimental Analysis, TREC Blog Track

Abstract

This paper systematically exploited various lexical features for opinion analysis on blog data using a statistical learning framework. Our experimental results using the TREC Blog track data show that all the features we explored effectively represent opinion expressions, and different classification strategies have a significant impact on opinion classification performance. We also present results when combining opinion analysis with the retrieval component for the task of retrieving relevant and opinionated blogs. Compared with the best results in the TREC evaluation, our system achieves reasonable performance, but does not rely on much human knowledge or deep level linguistic analysis.

Downloads

Published

2009-03-20

How to Cite

Liu, F., Li, B., & Liu, Y. (2009). Finding Opinionated Blogs Using Statistical Classifiers and Lexical Features. Proceedings of the International AAAI Conference on Web and Social Media, 3(1), 254-257. Retrieved from https://ojs.aaai.org/index.php/ICWSM/article/view/13985