Sentiment Analysis on Twitter: A text Mining Approach to the Afghanistan Status Reviews

Abstract

Twitter has become a popular social media network where people express their opinions and views on political and other topics. Social media analysis of Twitter can be used to understand which sentiment and opinions are implicit in these social media data. The purpose of this paper is to present an approach of natural language pre-processing, text mining, and sentiment analysis techniques to analyze Twitter data related to Afghanistan through a case study. Our article analyzes the Twitter English data about Afghanistan. The value of the proposed approach was to understand the most discomforts and happiness of people, their opinions, and the country situation in the different time through a case study. We found that from 29 March 2018 to 12 Jun 2018 almost always negative comments are higher than positives while from 13 Jun 2018 to 21 Jun 2018 it is just opposite, the positive comments are higher than negative comments on Twitter. The reason for this was the interim peace for a few days that had taken place between Afghan government and the Taliban terrorist group. The outcomes of this research can help the palpitations, companies, and stockholders to use social media network as a great information source for their better political strategies and better business decision-making for their current and future intentions. It provides a feasible approach and a case study as an example to assist the researchers to apply the sentiment techniques more effectively.