Sentiment Analysis Using Machine Learning Algorithms

被引：8

作者：

Jemai, Fatma ^{[1
]}

Hayouni, Mohamed ^{[2
]}

Baccar, Sahbi ^{[3
]}

机构：

[1] Univ Jendouba, Higher Inst Comp Sci KEF, Kef, Tunisia

[2] Univ Carthage, Innovcom Res Lab, Higher Sch Commun Sup Com, Ariana, Tunisia

[3] CESI Grad Sch Engn, Rouen, France

来源：

IWCMC 2021: 2021 17TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC) | 2021年

关键词：

Machine Learning (ML); NLTK; Sentiment analysis(SA);

D O I：

10.1109/IWCMC51323.2021.9498965

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

This work aims at building a classifier able of predicting the polarity of a comment while using Machine Learning (ML) algorithms. Our work is essentially divided into three tasks: data extraction, processing and modelling. In order to build our model, we use the NLTK dataset. Then, we use text mining techniques to generate and process the variables. Based on a supervised probabilistic machine learning algorithm, we tended to create a classifier to classify our tweets into positive and negative sentiments then we opt for two experiments to evaluate the performance of our model. Compered to previous reported works, we achieve greater precision.

引用

页码：775 / 779

页数：5

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