A Novel Approach for Sentiment Analysis and Opinion Mining on Social Media Tweets

Abstract

Social media is a powerful tool for people to share their thoughts and feelings. People post their personal feelings and thoughts on any topic, person, policy or product for marketing or social attraction. This text information can be broken down into facts and opinions. Reflect people's feelings about government policies, products, national and international personalities, the constitution, incidents and events. Sentiment analysis is an area of study that analyzes people's opinions, ratings, attitudes and emotions in general from the written language. The texts of the reviews are edited to give an accurate description of the author's opinion on the subject. This paper proposes an analysis of the feelings of the writers about the subject and comments of the users of social networks in the context of Ethiopia with Facebook as a platform. In this paper, natural language processing (NLP) and machine learning (ML) based on a novel sentiment analysis and opinion mining framework used to conduct sentiment analysis and opinion mining of posts and user comments on social media via a Facebook application.