Sentiment Analysis Using Weight Model Based on SentiWordNet 3.0

被引：3

作者：

Kumar, Jitendra ^{[1
]}

Rout, Jitendra Kumar ^{[1
]}

Katiyar, Anshu ^{[1
]}

Jena, Sanjay Kumar ^{[1
]}

机构：

[1] Natl Inst Technol, Rourkela 769008, India

来源：

RECENT FINDINGS IN INTELLIGENT COMPUTING TECHNIQUES, VOL 3 | 2018年 / 709卷

关键词：

SentiWordNet; 3.0; Naive Bayes; Support vector machine; Logistic regression; Random forest; Pointwise mutual information;

D O I：

10.1007/978-981-10-8633-5_14

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Sentiment analysis also is known as opinion mining, is the process of analyzing the sentiment of public opinions, attitudes, comments, etc. In this paper, we present experimental results of NB, SVM, Random forest Machine Learning classifier using Weight model on three different datasets. The contributions of this paper are: (a) Generate feature weight model using SentiWordNet 3.0, (b) assign feature weight to every feature according to POS tag, and (c) suitable combination selection of adj, adv, verb, and noun to give better results.

引用

页码：131 / 139

页数：9

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