| Autor: |
Alanezi, Khaled, Albadi, Nuha, Hammad, Omar, Kurdi, Maram, Mishra, Shivakant |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1109/ASONAM55673.2022.10068664 |
| Popis: |
Online reviews have become essential for users to make informed decisions in everyday tasks ranging from planning summer vacations to purchasing groceries and making financial investments. A key problem in using online reviews is the overabundance of online that overwhelms the users. As a result, recommendation systems for providing helpfulness of reviews are being developed. This paper argues that cultural background is an important feature that impacts the nature of a review written by the user, and must be considered as a feature in assessing the helpfulness of online reviews. The paper provides an in-depth study of differences in online reviews written by users from different cultural backgrounds and how incorporating culture as a feature can lead to better review helpfulness recommendations. In particular, we analyze online reviews originating from two distinct cultural spheres, namely Arabic and Western cultures, for two different products, hotels and books. Our analysis demonstrates that the nature of reviews written by users differs based on their cultural backgrounds and that this difference varies based on the specific product being reviewed. Finally, we have developed six different review helpfulness recommendation models that demonstrate that taking culture into account leads to better recommendations. |
| Databáze: |
arXiv |
| Externí odkaz: |
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