An Improved SVM for Book Review Sentiment Polarity Analysis
Xinxin Guan, Yeli Li, Hechen Gong, Huayan Sun, Chufeng Zhou
Available Online December 2018.
- https://doi.org/10.2991/tlicsc-18.2018.23How to use a DOI?
- Support vector machine, Sentiment polarity analysis, Book review.
- In the internet age, whether a book has the value of reading, online comments play an important role. The data set in this paper is 4,000 comments obtained by the web crawler in Douban Reading. Based on the improved support vector machine (SVM) algorithm, a sentiment analysis has been given to these comments. The experimental results show that the improved SVM algorithm has a good effect on the rate and accuracy of sentiment polarity analysis of book reviews.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xinxin Guan AU - Yeli Li AU - Hechen Gong AU - Huayan Sun AU - Chufeng Zhou PY - 2018/12 DA - 2018/12 TI - An Improved SVM for Book Review Sentiment Polarity Analysis BT - 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018) PB - Atlantis Press SN - 1951-6851 UR - https://doi.org/10.2991/tlicsc-18.2018.23 DO - https://doi.org/10.2991/tlicsc-18.2018.23 ID - Guan2018/12 ER -