원문정보
초록
영어
Sentiment analysis is now in focus of companies to extract information from customers’ reviews. Usually the analysis classification is positive, negative and neutral. In this research we focus on the reviews for electronic products. The demographic and technical expertise level of consumers and reviewers are diverse hence there is difference in the way they review a product. Some review contains technical solutions, improvised ways of tackling problems, frustrations, joy etc. This differences in review calls for a wider classification scheme to contain these differences. We thereby introduced a five classification scheme namely positive, negative, advice, no sentiment and neutral at the sentence. We crawled data from amazon.com and used open source natural language processing tools to get the sentiment out of the review.
목차
1. Introduction
2. Literature Review
3. System Architecture
3.1. Classification Scheme
3.2. Feature Detection
3.3. Web Application
4. Experiment Results
4.1. Web Crawler
4.2. Sentence Extraction
4.3. Location Extraction
4.4. Sentiment Classification
4.5. Web Application.
5. Conclusion
Acknowledgements
References