Sentiment analysis on social media data using intelligent techniques

Title

Sentiment analysis on social media data using intelligent techniques

Creator

Panguila K.F.M.; Chandra J.

Description

Social media gives a simple method of communication technology for people to share their opinion, attraction and feeling. The aim of the paper is to extract various sentiment behaviour and will be used to make a strategic decision and also aids to categorize sentiment and affections of people as clear, contradictory or neutral. The data was preprocessed with the help of noise removal for removing the noise. The research work applied various techniques. After the noise removal, the popular classification methods were applied to extract the sentiment. The data were classified with the help of Multi-layer Perceptron (MLP), Convolutional Neural Networks (CNN). These two classification results were checked against the others classified such as Support Vector Machine (SVM), Random Forest, Decision tree, Nae Bayes, etc., based on the sentiment classification from twitter data and consumer affairs website. The proposed work found that Multi-layer Perceptron and Convolutional Neural Networks performs better than another Machine Learning Classifier. International Research Publication House.

Source

International Journal of Engineering Research and Technology, Vol-12, No. 3, pp. 440-445.

Date

2019-01-01

Publisher

International Research Publication House

Subject

Convolutional Neural Networks (CNN); Emotions; Machine Learning; Multi-layer Perceptron (MLP); Sentiment Analysis

Coverage

Panguila K.F.M., Department of Computer Science, CHRIST (Deemed to be University), India; Chandra J., Department of Computer Science, CHRIST (Deemed to be University), India

Rights

Restricted Access

Relation

ISSN: 9743154

Format

Online

Language

English

Type

Article

Identifier

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064499954&partnerID=40&md5=4f3bcc4336e5300c3c63560976d67b80