Online Social Network Analysis Using Machine Learning Techniques release_jlugwe3frfc3pb4c4z65a2e2eq

by K.C. Er. Hari

Published by Zenodo.

2017  

Abstract

People spent most of the time in Social Networks.People express their views and opinions in Social Networks.Opinions influence the behaviors of the people. Opinion is the subject of study of Sentiment analysis and Opinion Mining. Opinion expressed in Social network can be analyzed and assist in making decision choosing the most popular brands. Sometime predicting the future results too. Twitter is the most popular Social networking site where peopletweet about particular topics. Different Machine Learning Algorithms such as Naive Bayes, Support Vector Machine and Logistic Regression are used to extract and analyses the tweets data to provide the required results. In this paper, tweets are analyzed about the Android and IOS platform smartphone to determine and predict the most popular brand in market. Sentiment Index, Relative Strength and Post Rate approach are used for Prediction. The finding of this paper is useful in providing correct review for the Smartphones users to select the best Smartphones.
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Date   2017-08-22
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