Sentiment Analysis of Tweets Using Various Machine Learning Techniques

被引：0

作者：

Tariyal, Ankit ^{[1
]}

Goyal, Sachin ^{[1
]}

Tantububay, Neeraj ^{[1
]}

机构：

[1] RGPV, SOTI, Dept Informat Technol, Bhopal, India

来源：

2018 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATION AND TELECOMMUNICATION (ICACAT) | 2018年

关键词：

opinion mining; sentiment analysis; e-commerce; text mining; classification;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

In todays e-commerce market where online shopping and tourism is fastly growing so it very important to analyze such huge amount of large data present in web. So it is very important to create a method which classify the web data. Sentiment analysis is a method to classify the web data such as product reviews, views in to various polarities such a positive, negative or neutral. In this paper we classify the reviews by using various machine learning techniques, In this we create a various classification model and compute the performance of each models and select the best classification models based on their performance computation. We will use a combination of simple linear method (LDA), nonlinear methods (CART, KNN) and complex nonlinear methods (SVM, RF, C5.0).. (Abstract)

引用

页数：5

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