VLSP shared task: Sentiment analysis

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 first campaign in 2016 only focused on the sentiment polarity classification, 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. The paper describes the built datasets as well as the evaluation results of the systems participating to these campaigns.