Proceedings of the 2018 International Conference on Transportation & Logistics, Information & Communication, Smart City (TLICSC 2018)

An Improved SVM for Book Review Sentiment Polarity Analysis

Authors
Xinxin Guan, Yeli Li, Hechen Gong, Huayan Sun, Chufeng Zhou
Corresponding Author
Xinxin Guan
Available Online December 2018.
DOI
https://doi.org/10.2991/tlicsc-18.2018.23How to use a DOI?
Keywords
Support vector machine, Sentiment polarity analysis, Book review.
Abstract
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.

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Proceedings
Part of series
Advances in Intelligent Systems Research
Publication Date
December 2018
ISBN
978-94-6252-621-1
ISSN
1951-6851
DOI
https://doi.org/10.2991/tlicsc-18.2018.23How to use a DOI?
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
PB  - Atlantis Press
SP  - 139
EP  - 143
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  -