Document - A Multi-lingual Annotated Dataset for Aspect-Oriented Opinion Mining

2015

Conference article Open Access

A Multi-lingual Annotated Dataset for Aspect-Oriented Opinion Mining

Jimenez Zafra S., Berardi G., Esuli A., Marcheggiani D., Martin-Valdivia M. T., Moreo Fernández A.

opinion mining aspect mining multilingual

We present the Trip-MAML dataset, a Multi-Lingual dataset of hotel reviews that have been manually annotated at the sentence-level with Multi-Aspect sentiment labels. This dataset has been built as an extension of an existent English-only dataset, adding documents written in Italian and Spanish. We detail the dataset construction process, covering the data gathering, selection, and annotation. We present inter-annotator agreement figures and baseline experimental results, comparing the three languages. Trip-MAML is a multi-lingual dataset for aspect-oriented opinion mining that enables researchers (i) to face the problem on languages other than English and (ii) to the experiment the application of cross-lingual learning methods to the task

Source: Conference on Empirical Methods in Natural Language Processing, pp. 2533–2538, Lisbon, 17-21/0972015

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@inproceedings{oai:it.cnr:prodotti:345815,
	title = {A Multi-lingual Annotated Dataset for Aspect-Oriented Opinion Mining},
	author = {Jimenez Zafra S. and Berardi G. and Esuli A. and Marcheggiani D. and Martin-Valdivia M.  T. and Moreo Fernández A.},
	doi = {10.18653/v1/d15-1302},
	booktitle = {Conference on Empirical Methods in Natural Language Processing, pp. 2533–2538, Lisbon, 17-21/0972015},
	year = {2015}
}