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Effective Opinion Spam Detection: A Study on Review Metadata Versus Content

Journal of Data and Information Science 2020年第2期5卷 76-110页

作者： Ajay Rastogi Monica Mehrotra Syed Shafat Ali Department of Computer Science Jamia Millia IslamiaNew DelhiIndia

Purpose:This paper aims to analyze the effectiveness of two major types of features—metadata-based(behavioral)and content-based(textual)—in opinion spam ***/methodology/approach:Based on spam-detection perspectives,our approach works in three settings:review-centric(spam detection),reviewer-centric(spammer detection)and product-centric(spam-targeted product detection).Besides this,to negate any kind of classifier-bias,we employ four classifiers to get a better and unbiased reflection of the obtained *** addition,we have proposed a new set of features which are compared against some well-known related *** experiments performed on two real-world datasets show the effectiveness of different features in opinion spam ***:Our findings indicate that behavioral features are more efficient as well as effective than the textual to detect opinion spam across all three *** addition,models trained on hybrid features produce results quite similar to those trained on behavioral features than on the textual,further establishing the superiority of behavioral features as dominating indicators of opinion *** features used in this work provide improvement over existing features utilized in other related ***,the computation time analysis for feature extraction phase shows the better cost efficiency of behavioral features over the *** limitations:The analyses conducted in this paper are solely limited to two wellknown datasets,viz.,Yelp Zip and Yelp NYC of *** implications:The results obtained in this paper can be used to improve the detection of opinion spam,wherein the researchers may work on improving and developing feature engineering and selection techniques focused more on metadata ***/value:To the best of our knowledge,this study is the first of its kind which considers three perspectives(review,reviewer and product-centric)and four classifiers to analyze the effecti

关键词： Opinion spam Behavioral features textual features Review spammers Spam-targeted products

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