Emotion and opinion retrieval from social media in Arabic language: Survey
Huda Jamal Abdelhameed, Susana Muñoz-Hernández · 2017
In recent years, the use of Internet has become one of the daily activates in our life. Social networks constitute a major component of the Web and made a revolution. It includes social networks, blogs, forum discussions and micro-blogs. Users of social media generate a huge amount of comments on a daily basis. Due to this revolution, most researches are now focusing on extracting meaningful information from social media to better understand the user's attitude. Sentiment analysis and opinion mining are fields of text mining that focus on extracting and analyzing the emotions and opinions of the users with respect to specific topic. Many approaches are proposed to extract opinions and classify them based on its polarities as positive, negative or neutral. Most works on sentiment analysis are done over English language, but a few of them focused on Arabic language. In this paper, we review many researches concerned with sentiment analysis over social media in Arabic language, and analyzed them by their methods, tools, and techniques. In addition, many approaches used for sentiment classification are discussed.