Categorizing Review Helpfulness Using Abstract Dialectical Frameworks

Atefeh Keshavarzi Zafarghandi*, Davide Ceolin

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

Consumer reviews are a vital aspect of the decision-making process for both buyers and companies in the era of e-commerce and online shopping. However, the helpfulness of reviews varies widely, and the abundance of available information can make it difficult to identify the most informative ones. Therefore, categorizing product reviews based on their helpfulness is a critical task. Review helpfulness can be determined by considering several features, such as readability, sentiment, word count, and coherence between the sentiment and score of a review. This article proposes a method for categorizing review helpfulness based on readability and coherence. Our approach employs abstract dialectical frameworks (ADFs), which use interpretation-based semantics to evaluate the acceptability of arguments. We tailor a specific ADF to each review to assess its helpfulness and provide clear explanations for our labeling decisions. We use the grounded semantics of ADFs, which provides information that no one can argue against, to justify our labels and enhance the value of our process. Our method can also be used as a system to give feedback to the review authors on why their reviews may not be helpful and how they can improve them in the future by considering readability and coherence factors. Moreover, our method can work on both small and large data-sets, which may not be feasible with machine learning methods that require a lot of training data.

Original languageEnglish
Title of host publicationTrust Management XIV
Subtitle of host publication14th IFIP WG 11.11 International Conference on Trust Management, IFIPTM 2023, Amsterdam, The Netherlands, October 18–20, 2023, Proceedings
EditorsTim Muller, Carmen Fernandez-Gago, Davide Ceolin, Ehud Gudes, Nurit Gal-Oz
PublisherSpringer Science and Business Media Deutschland GmbH
Pages89-104
Number of pages16
ISBN (Electronic)9783031767142
ISBN (Print)9783031767135, 9783031767166
DOIs
Publication statusPublished - 2024
Event14th IFIP WG 11.11 International Conference on Trust Management, IFIPTM 2023 - Amsterdam, Netherlands
Duration: 19 Oct 202320 Oct 2023

Publication series

NameIFIP Advances in Information and Communication Technology
PublisherSpringer
Volume694 IFIP
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X
NameIFIPTM: IFIP International Conference on Trust Management
PublisherSpringer
Volume2023

Conference

Conference14th IFIP WG 11.11 International Conference on Trust Management, IFIPTM 2023
Country/TerritoryNetherlands
CityAmsterdam
Period19/10/2320/10/23

Bibliographical note

Publisher Copyright:
© IFIP International Federation for Information Processing 2024.

Keywords

  • Abstract dialectical frameworks
  • Explainable artificial intelligence
  • Online reviews

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