Can You Distinguish Truthful from Fake Reviews? User Analysis and Assistance Tool for Fake Review Detection

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dc.contributor.authorKim, Jeonghwanko
dc.contributor.authorKang, Junmoko
dc.contributor.authorShin, Suwonko
dc.contributor.authorMyaeng, Sung-Hyonko
dc.date.accessioned2021-11-23T06:47:32Z-
dc.date.available2021-11-23T06:47:32Z-
dc.date.created2021-11-14-
dc.date.created2021-11-14-
dc.date.issued2021-04-20-
dc.identifier.citationFirst Workshop on Bridging Human–Computer Interaction and Natural Language Processing, pp.53 - 59-
dc.identifier.urihttp://hdl.handle.net/10203/289412-
dc.description.abstractCustomer reviews are useful in providing an indirect, secondhand experience of a product. People often use reviews written by other customers as a guideline prior to purchasing a product. Such behavior signifies the authenticity of reviews in e-commerce platforms. However, fake reviews are increasingly becoming a hassle for both consumers and product owners. To address this issue, we propose You Only Need Gold (YONG), an essential information mining tool for detecting fake reviews and augmenting user discretion. Our experimental results show the poor human performance on fake review detection, substantially improved user capability given our tool, and the ultimate need for user reliance on the tool.-
dc.languageEnglish-
dc.publisherEACL-
dc.titleCan You Distinguish Truthful from Fake Reviews? User Analysis and Assistance Tool for Fake Review Detection-
dc.typeConference-
dc.identifier.scopusid2-s2.0-85123312500-
dc.type.rimsCONF-
dc.citation.beginningpage53-
dc.citation.endingpage59-
dc.citation.publicationnameFirst Workshop on Bridging Human–Computer Interaction and Natural Language Processing-
dc.identifier.conferencecountryUI-
dc.identifier.conferencelocationKiev (Online)-
dc.contributor.localauthorMyaeng, Sung-Hyon-
dc.contributor.nonIdAuthorKang, Junmo-
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CS-Conference Papers(학술회의논문)
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