Painsight: An Extendable Opinion Mining Framework for Detecting Pain Points Based on Online Customer Reviews

Yukyung Lee, Jaehee Kim, Doyoon Kim, Yookyung Kho, Younsun Kim, Pilsung Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

As the e-commerce market continues to expand and online transactions proliferate, customer reviews have emerged as a critical element in shaping the purchasing decisions of prospective buyers. Previous studies have endeavored to identify key aspects of customer reviews through the development of sentiment analysis models and topic models. However, extracting specific dissatisfaction factors remains a challenging task. In this study, we delineate the pain point detection problem and propose Painsight, an unsupervised framework for automatically extracting distinct dissatisfaction factors from customer reviews without relying on ground truth labels. Painsight employs pre-trained language models to construct sentiment analysis and topic models, leveraging attribution scores derived from model gradients to extract dissatisfaction factors. Upon application of the proposed methodology to customer review data spanning five product categories, we successfully identified and categorized dissatisfaction factors within each group, as well as isolated factors for each type. Notably, Painsight outperformed benchmark methods, achieving substantial performance enhancements and exceptional results in human evaluations.

Original languageEnglish
Title of host publicationWASSA 2023 - 13th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Proceedings of the Workshop
EditorsJeremy Barnes, Orphee De Clercq, Roman Klinger
PublisherAssociation for Computational Linguistics (ACL)
Pages215-227
Number of pages13
ISBN (Electronic)9781959429876
Publication statusPublished - 2023
Event13th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2023 - Toronto, Canada
Duration: 2023 Jul 14 → …

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)0736-587X

Conference

Conference13th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2023
Country/TerritoryCanada
CityToronto
Period23/7/14 → …

Bibliographical note

Publisher Copyright:
© 2023 Association for Computational Linguistics.

ASJC Scopus subject areas

  • Computer Science Applications
  • Linguistics and Language
  • Language and Linguistics

Fingerprint

Dive into the research topics of 'Painsight: An Extendable Opinion Mining Framework for Detecting Pain Points Based on Online Customer Reviews'. Together they form a unique fingerprint.

Cite this