An Opinion Analysis Tool for Colloquial and Standard Arabic

Social networks and users’ interactions are distinct features for the current Web. They constitute a fundamental part of Web 2.0, where people produce, disseminate, and consume information in new interactive forms where users are not only passive information receivers. Social media succeed to attract a large portion of online users, which explains the explosive growth of social media in terms of comments, reviews, blogs, microblogs, Twitters, and postings in social network sites. In this scope, sentiment analysis research field refers to the analysis of people’s sentiments, opinions, attitudes, and emotions towards events, products, companies, individuals, issues, sport teams ...etc. Facebook, and YouTube are within the top 3 sites used in many Middle Eastern (ME) countries, and the world. Therefore a huge volume of Arabic comments and reviews are generated daily about different aspects of life in this part of the world. Modern Standard Arabic (MSA) is used mainly in media (Newspapers, Journals, TV and Radio), academic institution, and to some extent in social media. While colloquial Arabic is used by the public in their conversations, chatting, etc.. Analysis of social networks in ME countries shows that both MSA and colloquial or slang languages are used. The aim of this study is to build a novel sentiment analysis tool called colloquial Non-Standard Arabic Modern Standard Arabic-Sentiment Analysis Tool (CNSAMSA-SAT) dedicated to both colloquial Arabic and MSA. A large number of Arabic collected comments and reviews from social media were tokenized and analyzed to build polarity lexicons which constitute an essential part of CNSA-MSA-SAT. Each Arabic collected comment and review is manually assigned to one of the three polarity values: (positive, negative, and neutral). Further, each collected review or comment is added to CNSA-MSA-SAT and is then assigned to one of the three polarities values based on algorithms developed for this purpose.