Identifying Helpful Sentences in Product Reviews

Iftah Gamzu, Hila Gonen, Gilad Kutiel, Ran Levy, Eugene Agichtein


Abstract
In recent years online shopping has gained momentum and became an important venue for customers wishing to save time and simplify their shopping process. A key advantage of shopping online is the ability to read what other customers are saying about products of interest. In this work, we aim to maintain this advantage in situations where extreme brevity is needed, for example, when shopping by voice. We suggest a novel task of extracting a single representative helpful sentence from a set of reviews for a given product. The selected sentence should meet two conditions: first, it should be helpful for a purchase decision and second, the opinion it expresses should be supported by multiple reviewers. This task is closely related to the task of Multi Document Summarization in the product reviews domain but differs in its objective and its level of conciseness. We collect a dataset in English of sentence helpfulness scores via crowd-sourcing and demonstrate its reliability despite the inherent subjectivity involved. Next, we describe a complete model that extracts representative helpful sentences with positive and negative sentiment towards the product and demonstrate that it outperforms several baselines.
Anthology ID:
2021.naacl-main.55
Volume:
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
June
Year:
2021
Address:
Online
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
678–691
Language:
URL:
https://aclanthology.org/2021.naacl-main.55
DOI:
10.18653/v1/2021.naacl-main.55
Bibkey:
Cite (ACL):
Iftah Gamzu, Hila Gonen, Gilad Kutiel, Ran Levy, and Eugene Agichtein. 2021. Identifying Helpful Sentences in Product Reviews. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 678–691, Online. Association for Computational Linguistics.
Cite (Informal):
Identifying Helpful Sentences in Product Reviews (Gamzu et al., NAACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.naacl-main.55.pdf
Video:
 https://aclanthology.org/2021.naacl-main.55.mp4