Review spamicity based on rank and content of the review

Nowadays the volume of on-line sales has been increasing in a tremendous pace. Online reviews can help people getting more information about any store or product and are source of information for the potential customers before deciding to purchase a product. Subsequently, websites containing customer reviews are becoming targets of opinion spam. It is important to detect opinion spam to enable the real opinion of the product to surface. Hence, we propose an efficient and effective Semantic technique, SentiWordNet lexicon and a tool, Word Count and a method known as Counting method, to find spamicity of the reviews based on the content and rating of the reviews. The experimental results shows that the proposed technique has comparatively effective spamicity detection than other technique based on the rating and content of the reviews.