Nowadays, a lot of companies aim to tap into social media networking in order to maximize their profit by endorsing their products or services and to improve their brand names. The development of Web 2.0, has permitted Internet users to post, share and exchange their own self-generated opinions or thoughts on various topics on different websites. A large amount of data containing useful information concerning preferences of the consumers is generated from a variety of sources such as reviews, posts, microblogs or online digital markets. Furthermore, more and more review websites are established globally (Yelp, TripAdvisor, etc.) and most of them allow users to digitally evaluate about the products or services that they have consumed. The produced information (evaluations) which is generated rapidly can be large and generally modifies consumers’ behavior. However, in most of the cases, the involved companies or stakeholders cannot follow these modifications due to humans’ physical or mental restrictions. There are various approaches to face this problem with sentiment analysis being the preferred one. This special issue is aimed at theoretical or experimental works on Sentiment Analysis in social media and review webpages, especially for languages with limited resources. Also, it focuses on methods for analyzing social behaviors, processing linguistic phenomena (negation, sarcasm, etc.), hate-speech detection, fine-grained sentiment analysis, identification of psychological states such as depression, domain-dependent information, transfer learning issues, multilingual aspects, personalized sentiment analysis, etc.