Visible to the public A Spam Review Detection Method by Verifying Consistency among Multiple Review Sites

TitleA Spam Review Detection Method by Verifying Consistency among Multiple Review Sites
Publication TypeConference Paper
Year of Publication2019
AuthorsYao, Chuhao, Wang, Jiahong, Kodama, Eiichiro
Conference Name2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)
ISBN Number978-1-7281-2058-4
KeywordsConferences, consistency, consistency verification, Human Behavior, human factors, Internet, Metrics, Multiple review sites, performance evaluation, pubcrawl, reliability, review information, review sites, Scalability, sentiment analysis, Software, spam detection, spam review, Spam review detection, unsolicited e-mail, user purchasing behavior, user reviews, Web sites, websites

In recent years, websites that incorporate user reviews, such as Amazon, IMDB and YELP, have become exceedingly popular. As an important factor affecting users purchasing behavior, review information has been becoming increasingly important, and accordingly, the reliability of review information becomes an important issue. This paper proposes a method to more accurately detect the appearance period of spam reviews and to identify the spam reviews by verifying the consistency of review information among multiple review sites. Evaluation experiments were conducted to show the accuracy of the detection results, and compared the newly proposed method with our previously proposed method.

Citation Keyyao_spam_2019