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ROCLING-2021 Shared Task: Dimensional Sentiment Analysis for Educational Texts

2021-10-01ROCLING 2021Unverified0· sign in to hype

Liang-Chih Yu, Jin Wang, Bo Peng, Chu-Ren Huang

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Abstract

This paper presents the ROCLING 2021 shared task on dimensional sentiment analysis for educational texts which seeks to identify a real-value sentiment score of self-evaluation comments written by Chinese students in the both valence and arousal dimensions. Valence represents the degree of pleasant and unpleasant (or positive and negative) feelings, and arousal represents the degree of excitement and calm. Of the 7 teams registered for this shared task for two-dimensional sentiment analysis, 6 submitted results. We expected that this evaluation campaign could produce more advanced dimensional sentiment analysis techniques for the educational domain. All data sets with gold standards and scoring script are made publicly available to researchers.

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