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            <title>Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue</title>
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            <namePart type="given">Tatsuya</namePart>
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    <abstract>User reviews on e-commerce and review sites are crucial for making purchase decisions, although creating detailed reviews is time-consuming and labor-intensive. In this study, we propose a novel use of dialogue systems to facilitate user review creation by generating reviews from information gathered during interview dialogues with users. To validate our approach, we implemented our system using GPT-4 and conducted comparative experiments from the perspectives of system users and review readers. The results indicate that participants who used our system rated their interactions positively. Additionally, reviews generated by our system required less editing to achieve user satisfaction compared to those by the baseline. We also evaluated the reviews from the readers’ perspective and found that our system-generated reviews are more helpful than those written by humans. Despite challenges with the fluency of the generated reviews, our method offers a promising new approach to review writing.</abstract>
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    <identifier type="doi">10.18653/v1/2024.sigdial-1.37</identifier>
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%0 Conference Proceedings
%T User Review Writing via Interview with Dialogue Systems
%A Tanaka, Yoshiki
%A Inaba, Michimasa
%Y Kawahara, Tatsuya
%Y Demberg, Vera
%Y Ultes, Stefan
%Y Inoue, Koji
%Y Mehri, Shikib
%Y Howcroft, David
%Y Komatani, Kazunori
%S Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue
%D 2024
%8 September
%I Association for Computational Linguistics
%C Kyoto, Japan
%F tanaka-inaba-2024-user
%X User reviews on e-commerce and review sites are crucial for making purchase decisions, although creating detailed reviews is time-consuming and labor-intensive. In this study, we propose a novel use of dialogue systems to facilitate user review creation by generating reviews from information gathered during interview dialogues with users. To validate our approach, we implemented our system using GPT-4 and conducted comparative experiments from the perspectives of system users and review readers. The results indicate that participants who used our system rated their interactions positively. Additionally, reviews generated by our system required less editing to achieve user satisfaction compared to those by the baseline. We also evaluated the reviews from the readers’ perspective and found that our system-generated reviews are more helpful than those written by humans. Despite challenges with the fluency of the generated reviews, our method offers a promising new approach to review writing.
%R 10.18653/v1/2024.sigdial-1.37
%U https://aclanthology.org/2024.sigdial-1.37
%U https://doi.org/10.18653/v1/2024.sigdial-1.37
%P 428-439

Markdown (Informal)

[User Review Writing via Interview with Dialogue Systems](https://aclanthology.org/2024.sigdial-1.37) (Tanaka & Inaba, SIGDIAL 2024)

• User Review Writing via Interview with Dialogue Systems (Tanaka & Inaba, SIGDIAL 2024)

ACL

• Yoshiki Tanaka and Michimasa Inaba. 2024. User Review Writing via Interview with Dialogue Systems. In Proceedings of the 25th Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 428–439, Kyoto, Japan. Association for Computational Linguistics.