An Evaluation of Sentiment Analysis in Online Reviews using FRN Algorithm

I. Hemalatha, G. P. Saradhi Varma, A . Govardhan


The internet is rich in directional text (i.e., text containing opinions and emotions). World Wide Web provides volumes of text-based data about consumer preferences, stored in online review websites, web forums, blogs, etc. Sentiment analysis is a technique to classify people’s opinions in product reviews, blogs or social networks and has emerged as a method for mining opinions from such text archives. It uses machine learning methods combined with linguistic attributes/features in order to identify among other things the sentiment polarity (e.g., positive, negative, and neutral). The authors investigated supervised learning by incorporating linguistic rules and constraints that could improve the performance of calculations and classifications.

Keywords: Opinions, sentiment analysis, machine learning

Full Text:



Abbasi A, Chen H. CyberGate: A system and design framework for text analysis of computer mediated communication. MIS Quarterly. 2008; 32(4): 811–37p.

Abbasi A, Chen H, Thoms S, et al. Affect analysis of web forums and blogs using correlation ensembles. IEEE Trans. Knowledge and Data Eng. Sept. 2008; 20(9): 1168–80p.

Abbasi A, Chen H, Salem A. Sentiment analysis in multiple languages: Feature selection for opinion classification in web forums. ACM Trans. Information Systems. 2008; 26(3): 12.

Argamon S, Whitelaw C, Chase P, et al. Stylistic text classification using functional lexical features. J. Am. Soc. Information Science and Technology. 2008; 58(6): 802–22p.

Balakrishnan PV, Gupta R, Jacobs VS. Development of hybrid genetic algorithms for product line designs. IEEE Trans. Systems, Man, and Cybernetics. Feb. 2004; 34(1): 468–83p.

Burgun A, Bodenreider O. Comparing terms, concepts, and semantic classes in WordNet and the unified medical language system. Proc. North Am. Assoc.Computational Linguistics Workshop. 2001; 77–82p.

Cui H, Mittal V, Datar M. Comparative experiments on sentiment classification for online product reviews. Proc. 21st AAAI Conf. Artificial Intelligence. 2006; 1265–70p.

Das SR, Chen MY. Yahoo! for Amazon: Sentiment extraction from small talk onthe web. Management Science. 2007; 53(9): 1375–88p.

Esuli A, Sebastiani F. SentiWordNet: A publicly available lexical resource for opinion mining. Proc. Fifth Conf. Language Resources and Evaluation. 2006; 417–22p.


This site has been shifted to