Sentimental Analysis Using Fuzzy and Naive Bayes

被引：0

作者：

Mehra, Ruchi ^{[1
]}

Bedi, Mandeep Kaur ^{[1
]}

Singh, Gagandeep ^{[1
]}

Arora, Raman ^{[1
]}

Bala, Tannu ^{[1
]}

Saxena, Sunny ^{[1
]}

机构：

[1] Webtunix Solut Pvt Ltd, Mohali, India

来源：

2017 INTERNATIONAL CONFERENCE ON COMPUTING METHODOLOGIES AND COMMUNICATION (ICCMC) | 2017年

关键词：

Sentiment analysis; opinion mining; classification; machine learning; Natural language processing; deep learning; neural networks; Artificial Intelligence; Behaviour Analysis;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Sentimental Analysis is the best way to judge people's opinion regarding a particular post. In this paper we present analysis for sentiment behavior of Twitter data. The proposed work utilizes the naive Bayes and fuzzy Classifier to classify Tweets into positive, negative or neural behavior of a particular person. We present experimental evaluation of our dataset and classification results which proved that combined proposed method is more efficient in terms of Accuracy, Precision and Recall.

引用

页码：945 / 950

页数：6

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