Abstract This paper is a report of a review on sentiment analysis in social media that explored the methods, social media platform used and its application. Social media contain a large amount of raw data that has been uploaded by users in the form of text, videos, photos and audio. The data can be converted into valuable information by using sentiment analysis. A systematic review of studies published between 2014 to 2019 was undertaken using the following trusted and credible database including ACM, Emerald Insight, IEEE Xplore, Science Direct and Scopus. After the initial and in-depth screening of paper, 24 out of 77 articles have been chosen from the review process. The articles have been reviewed based on the aim of the study. The result shows most of the articles applied opinion-lexicon method to analyses text sentiment in social media, extracted data on microblogging site mainly Twitter and sentiment analysis application can be seen in world events, healthcare, politics and business.
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Sentiment Analysis in Social Media and Its Application: Systematic Literature Review
Semantic Scholar · Computer Science · 2019
Abstract
Abstract This paper is a report of a review on sentiment analysis in social media that explored the methods, social media platform used and its application. Social media contain a large amount of raw data that has been uploaded by users in the form of text, videos, photos and audio. The data can be converted into valuable information by using sentiment analysis. A systematic review of studies published between 2014 to 2019 was undertaken using the following trusted and credible database including ACM, Emerald Insight, IEEE Xplore, Science Direct and Scopus. After the initial and in-depth screening of paper, 24 out of 77 articles have been chosen from the review process. The articles have been reviewed based on the aim of the study. The result shows most of the articles applied opinion-lexicon method to analyses text sentiment in social media, extracted data on microblogging site mainly Twitter and sentiment analysis application can be seen in world events, healthcare, politics and business.