{'fraction_non_alphanumeric': 0.013374485596707819, 'fraction_numerical': 0.0, 'mean_word_length': 5.006172839506172, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Opinion Mining based Identifying Deceptive Reviews

People nowadays are using online reviews to purchase products online. These reviews affect the sales of the product and play a major role in the company’s profits. The gradual increase in the number of social networks is paving the way for the checking of truthfulness of various reviews that are conducted online. Also, some cyber criminals are used to target some of the products, organizations or even individuals. The tasks performed by such individuals are called as Opinion Spamming and the individuals are called as Opinion Spammers. This process of Opinion Spamming not only damages the money and reputation of the organizations. But also plays a crucial role in the politics. As technology is getting highly sophisticated, it is becoming very difficult to identify such Spamming activities. This paper concentrates on various detection techniques of Opinion Spamming and suggests some of the ways to prevent it.