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VLSP SHARED TASK: SENTIMENT ANALYSIS

Huyen T M Nguyen, Hung V Nguyen, Quyen T Ngo, Luong X Vu, Vu Mai Tran, Bach X Ngo, Cuong A Le

Abstract


Sentiment analysis is a natural language processing (NLP) task of identifying or
extracting the sentiment content of a text unit. This task has become an active research topic since the early 2000s. During the two last editions of the VLSP workshop series, the shared task on Sentiment Analysis (SA) for Vietnamese has been organized in order to provide an objective evaluation measurement about the performance (quality) of sentiment analysis tools, and encourage
the development of Vietnamese sentiment analysis systems, as well as to provide benchmark datasets for this task. The rst campaign in 2016 only focused on the sentiment polarity classication, with a dataset containing reviews of electronic products. The second campaign in 2018 addressed the problem of Aspect Based Sentiment Analysis (ABSA) for Vietnamese, by providing two datasets containing reviews in restaurant and hotel domains. These data are accessible for research purpose via the VLSP website vlsp.org.vn/resources. This paper describes the built datasets as well as the evaluation results of the systems participating to these campaigns.


Keywords


aspect based sentiment analysis, evaluation, opinion mining, sentiment analysis, shared task, Vietnamese, VLSP workshop

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DOI: https://doi.org/10.15625/1813-9663/34/4/13160

Journal of Computer Science and Cybernetics ISSN: 1813-9663

Published by Vietnam Academy of Science and Technology