Nissrine Bensouda
ABSTRACT
Thanks to the rapid advances in Internet technologies in the last decade, there has been an exponential growth in the development and use of a large variety of social media platforms. Today, these online spaces are widely around the world as they enable people to generate content and share their opinions about different topics, products and services. Given the valuable information that they include, these online reviews are often one of the primary sources up on which a customer's decision to purchase a product or a service is based. These opinions are also a valuable source of information that businesses resort to in order to determine public opinion on their goods and services. Nevertheless, the truthfulness or veracity of these opinions is questionable. In fact, many of these are opinion spams whose purpose is merely to destroy the reputation of a company's products or services or to promote another company's low quality goods. The objective of this paper is, therefore, to review the most important works that have been addressed opinion spam detection. The findings of the study revealed that the approaches, which were based on machine learning and natural language processing techniques, can be classified into three categories: linguistic, behavioral and statistical.
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