What Online Reviewer Behaviors Really Matter? Effects of Verbal and Nonverbal Behaviors on Detection of Fake Online Reviews
被引:197
作者:
Zhang, Dongsong
论文数: 0引用数: 0
h-index: 0
机构:
Jinan Univ, Int Business Sch, Guangzhou Shi, Guangdong Sheng, Peoples R China
Univ Maryland Baltimore Cty, Dept Informat Syst, Baltimore, MD 21228 USAJinan Univ, Int Business Sch, Guangzhou Shi, Guangdong Sheng, Peoples R China
Zhang, Dongsong
[1
,2
]
Zhou, Lina
论文数: 0引用数: 0
h-index: 0
机构:
Univ Maryland Baltimore Cty, Dept Informat Syst, Baltimore, MD 21228 USAJinan Univ, Int Business Sch, Guangzhou Shi, Guangdong Sheng, Peoples R China
Zhou, Lina
[2
]
Kehoe, Juan Luo
论文数: 0引用数: 0
h-index: 0
机构:
Univ Maryland Baltimore Cty, Dept Informat Syst, Baltimore, MD 21228 USAJinan Univ, Int Business Sch, Guangzhou Shi, Guangdong Sheng, Peoples R China
Kehoe, Juan Luo
[2
]
Kilic, Isil Yakut
论文数: 0引用数: 0
h-index: 0
机构:
Univ Maryland Baltimore Cty, Dept Informat Syst, Baltimore, MD 21228 USAJinan Univ, Int Business Sch, Guangzhou Shi, Guangdong Sheng, Peoples R China
Kilic, Isil Yakut
[2
]
机构:
[1] Jinan Univ, Int Business Sch, Guangzhou Shi, Guangdong Sheng, Peoples R China
The value and credibility of online consumer reviews are compromised by significantly increasing yet difficult-to-identify fake reviews. Extant models for automated online fake review detection rely heavily on verbal behaviors of reviewers while largely ignoring their nonverbal behaviors. This research identifies a variety of nonverbal behavioral features of online reviewers and examines their relative importance for the detection of fake reviews in comparison to that of verbal behavioral features. The results of an empirical evaluation using real-world online reviews reveal that incorporating nonverbal features of reviewers can significantly improve the performance of online fake review detection models. Moreover, compared with verbal features, nonverbal features of reviewers are shown to be more important for fake review detection. Furthermore, model pruning based on a sensitivity analysis improves the parsimony of the developed fake review detection model without sacrificing its performance.
引用
收藏
页码:456 / 481
页数:26
相关论文
共 69 条
[61]
Wakade S., 2013, EMERGING PARADIGMS M, P471, DOI DOI 10.1007/978-3-642-28699-518
[62]
Wu Guangyu., 2010, Proceedings of the First Workshop on Social Media Analytics, P10
机构:
City Univ Hong Kong, Dept Informat Syst, Hong Kong, Hong Kong, Peoples R ChinaUniv Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia
Lau, Raymond Y. K.
Song, Dawei
论文数: 0引用数: 0
h-index: 0
机构:
Robert Gordon Univ, Sch Comp, Aberdeen AB9 1FR, ScotlandUniv Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia
机构:
City Univ Hong Kong, Dept Informat Syst, Hong Kong, Hong Kong, Peoples R ChinaUniv Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia
机构:
Univ So Calif, Marshall Sch Business, Los Angeles, CA 90089 USAUniv So Calif, Marshall Sch Business, Los Angeles, CA 90089 USA
Zhu, Feng
Zhang, Xiaoquan
论文数: 0引用数: 0
h-index: 0
机构:
Hong Kong Univ Sci & Technol, HKUST Business Sch, Hong Kong, Hong Kong, Peoples R China
MIT, Ctr Digital Business, Cambridge, MA 02139 USAUniv So Calif, Marshall Sch Business, Los Angeles, CA 90089 USA
机构:
City Univ Hong Kong, Dept Informat Syst, Hong Kong, Hong Kong, Peoples R ChinaUniv Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia
Lau, Raymond Y. K.
Song, Dawei
论文数: 0引用数: 0
h-index: 0
机构:
Robert Gordon Univ, Sch Comp, Aberdeen AB9 1FR, ScotlandUniv Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia
机构:
City Univ Hong Kong, Dept Informat Syst, Hong Kong, Hong Kong, Peoples R ChinaUniv Queensland, Sch Informat Technol & Elect Engn, Brisbane, Qld 4072, Australia
机构:
Univ So Calif, Marshall Sch Business, Los Angeles, CA 90089 USAUniv So Calif, Marshall Sch Business, Los Angeles, CA 90089 USA
Zhu, Feng
Zhang, Xiaoquan
论文数: 0引用数: 0
h-index: 0
机构:
Hong Kong Univ Sci & Technol, HKUST Business Sch, Hong Kong, Hong Kong, Peoples R China
MIT, Ctr Digital Business, Cambridge, MA 02139 USAUniv So Calif, Marshall Sch Business, Los Angeles, CA 90089 USA