Sentiment analysis using product review data

被引：13

作者：

Fang X. ^{[1
]}

Zhan J. ^{[1
]}

机构：

[1] Department of Computer Science, North Carolina A&T State University, Greensboro, NC

来源：

Journal of Big Data | 2015年 / 2卷 / 01期

基金：

美国国家科学基金会;

关键词：

Sentiment analysis; Sentiment polarity categorization; Natural language processing; Product reviews;

D O I：

10.1186/s40537-015-0015-2

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Sentiment analysis or opinion mining is one of the major tasks of NLP (Natural Language Processing). Sentiment analysis has gain much attention in recent years. In this paper, we aim to tackle the problem of sentiment polarity categorization, which is one of the fundamental problems of sentiment analysis. A general process for sentiment polarity categorization is proposed with detailed process descriptions. Data used in this study are online product reviews collected from Amazon.com. Experiments for both sentence-level categorization and review-level categorization are performed with promising outcomes. At last, we also give insight into our future work on sentiment analysis. © 2015, Fang and Zhan; licensee Springer.

引用

共 26 条

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