Open AccessSentiment Analysis of Facebook Posts using Hybrid Method
Author(s) -
Swarnangini Sinha,
Kanak Saxena,
Nisheeth Joshi
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1969.078219
Subject(s) - sentiment analysis , social media , computer science , support vector machine , artificial intelligence , lexical analysis , natural language processing , world wide web
Social Media is a popular medium of communication amongst youngsters to remain connected with their friends. Facebook is one of the most preferred Social Media Sites which store the gigantic amount of data which can be explored for Sentiment Analysis. In this study, we have applied hybrid analysis approach which combines the best features of a lexical analysis and SVM machine learning classification algorithm on Facebook Posts. The analysis is further improved by incorporating language discourse features to detect intensity of sentiment and the prominent emotions expressed through these posts.