@inproceedings{apidianaki-etal-2016-datasets,
title = "Datasets for Aspect-Based Sentiment Analysis in {F}rench",
author = "Apidianaki, Marianna and
Tannier, Xavier and
Richart, C{\'e}cile",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Goggi, Sara and
Grobelnik, Marko and
Maegaard, Bente and
Mariani, Joseph and
Mazo, Helene and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
month = may,
year = "2016",
address = "Portoro{\v{z}}, Slovenia",
publisher = "European Language Resources Association (ELRA)",
url = "https://aclanthology.org/L16-1179",
pages = "1122--1126",
abstract = "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) dedicated to out-of-domain evaluation. 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.",
}
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%0 Conference Proceedings
%T Datasets for Aspect-Based Sentiment Analysis in French
%A Apidianaki, Marianna
%A Tannier, Xavier
%A Richart, Cécile
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Grobelnik, Marko
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Helene
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 May
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F apidianaki-etal-2016-datasets
%X 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) dedicated to out-of-domain evaluation. 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.
%U https://aclanthology.org/L16-1179
%P 1122-1126
Markdown (Informal)
[Datasets for Aspect-Based Sentiment Analysis in French](https://aclanthology.org/L16-1179) (Apidianaki et al., LREC 2016)
ACL
- Marianna Apidianaki, Xavier Tannier, and Cécile Richart. 2016. Datasets for Aspect-Based Sentiment Analysis in French. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 1122–1126, Portorož, Slovenia. European Language Resources Association (ELRA).