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        <title>Building Large-Scale English and Korean Datasets for Aspect-Level Sentiment Analysis in Automotive Domain</title>
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    <abstract>We release large-scale datasets of users’ comments in two languages, English and Korean, for aspect-level sentiment analysis in automotive domain. The datasets consist of 58,000+ commentaspect pairs, which are the largest compared to existing datasets. In addition, this work covers new language (i.e., Korean) along with English for aspect-level sentiment analysis. We build the datasets from automotive domain to enable users (e.g., marketers in automotive companies) to analyze the voice of customers on automobiles. We also provide baseline performances for future work by evaluating recent models on the released datasets.</abstract>
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%0 Conference Proceedings
%T Building Large-Scale English and Korean Datasets for Aspect-Level Sentiment Analysis in Automotive Domain
%A Hyun, Dongmin
%A Cho, Junsu
%A Yu, Hwanjo
%Y Scott, Donia
%Y Bel, Nuria
%Y Zong, Chengqing
%S Proceedings of the 28th International Conference on Computational Linguistics
%D 2020
%8 December
%I International Committee on Computational Linguistics
%C Barcelona, Spain (Online)
%F hyun-etal-2020-building
%X We release large-scale datasets of users’ comments in two languages, English and Korean, for aspect-level sentiment analysis in automotive domain. The datasets consist of 58,000+ commentaspect pairs, which are the largest compared to existing datasets. In addition, this work covers new language (i.e., Korean) along with English for aspect-level sentiment analysis. We build the datasets from automotive domain to enable users (e.g., marketers in automotive companies) to analyze the voice of customers on automobiles. We also provide baseline performances for future work by evaluating recent models on the released datasets.
%R 10.18653/v1/2020.coling-main.83
%U https://aclanthology.org/2020.coling-main.83
%U https://doi.org/10.18653/v1/2020.coling-main.83
%P 961-966

Markdown (Informal)

[Building Large-Scale English and Korean Datasets for Aspect-Level Sentiment Analysis in Automotive Domain](https://aclanthology.org/2020.coling-main.83) (Hyun et al., COLING 2020)

• Building Large-Scale English and Korean Datasets for Aspect-Level Sentiment Analysis in Automotive Domain (Hyun et al., COLING 2020)

ACL

• Dongmin Hyun, Junsu Cho, and Hwanjo Yu. 2020. Building Large-Scale English and Korean Datasets for Aspect-Level Sentiment Analysis in Automotive Domain. In Proceedings of the 28th International Conference on Computational Linguistics, pages 961–966, Barcelona, Spain (Online). International Committee on Computational Linguistics.