Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/80816
Title: Let's vote to classify authentic and manipulative online reviews : the role of comprehensibility, informativeness and writing style
Authors: Banerjee, Snehasish
Chua, Alton Y. K.
Kim, Jung-Jae
Keywords: Online reviews
Authentic
Manipulative
Classification
Voting
Comprehensibility
Informativeness
Writing style
Issue Date: 2015
Source: Banerjee, S., Chua, A. Y. K., & Kim, J. J. (2015). Let's vote to classify authentic and manipulative online reviews: The role of comprehensibility, informativeness and writing style. 2015 Science and Information Conference (SAI), 77-83 .
Conference: Science and Information Conference (SAI) (2015:London)
Abstract: Scholars increasingly seek to investigate differences between authentic and manipulative online reviews. A common line of research argues that authentic and manipulative reviews are distinguishable based on three textual characteristics, namely, comprehensibility, informativeness and writing style. Although recent studies have analyzed differences between authentic and manipulative reviews in terms of these textual characteristics, they often lack in terms of methodological rigor. For one, datasets used for analysis are not always representative. Moreover, only few machine learning algorithms are used to classify authentic and manipulative reviews. Recognizing the value of methodological rigor, this paper extends prior studies by examining textual differences between authentic and manipulative reviews using a more representative dataset. Moreover, authentic and manipulative reviews were classified using a voting among multiple classifiers that had been used in recent literature. The implications of the results are discussed.
URI: https://hdl.handle.net/10356/80816
http://hdl.handle.net/10220/38862
DOI: 10.1109/SAI.2015.7237129
Schools: Wee Kim Wee School of Communication and Information 
School of Computer Science and Engineering 
Rights: © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://www.dx.doi.org/10.1109/SAI.2015.7237129].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers
WKWSCI Conference Papers

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