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Communication Dans Un Congrès Année : 2016

Datasets for Aspect-Based Sentiment Analysis in French

Résumé

Aspect Based Sentiment Analysis (ABSA) is the task of mining and summarizing opinions from text about specific entities and their aspects. This article describes two datasets for the development and testing of ABSA systems for French which comprise user reviews annotated with relevant entities, aspects and polarity values. The first dataset contains 457~restaurant reviews (2365~sentences) for training and testing ABSA systems, while the second contains 162~museum reviews (655~sentences) for testing in this previously unseen domain for which training data is not available. Both datasets were built as part of SemEval-2016 Task~5 ``Aspect-Based Sentiment Analysis'' where seven different languages were represented, and are publicly available for research purposes. This article provides examples and statistics by annotation type, summarizes the annotation guidelines and discusses their cross-lingual applicability. It also explains how the data was used for evaluation in the SemEval ABSA task and briefly presents the results obtained for French.
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Dates et versions

hal-01838536 , version 1 (13-07-2018)

Identifiants

  • HAL Id : hal-01838536 , version 1

Citer

Marianna Apidianaki, Xavier Tannier, Cécile Richart. Datasets for Aspect-Based Sentiment Analysis in French. International Conference on Language Resources and Evaluation, Jan 2016, Portorož, Slovenia. ⟨hal-01838536⟩
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