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Ciron: a New Benchmark Dataset for Chinese Irony Detection

Xiang, Rong and Gao, Xuefeng and Long, Yunfei and Li, Anran and Chersoni, Emmanuele and Lu, Qin and Huang, Chu-Ren (2020) Ciron: a New Benchmark Dataset for Chinese Irony Detection. In: 12th Language Resources and Evaluation Conference, 2020-05-11 - 2020-05-16, Marseille, France.

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Automatic Chinese irony detection is a challenging task, and it has a strong impact on linguistic research. However, Chinese irony detection often lacks labeled benchmark datasets. In this paper, we introduce Ciron, the first Chinese benchmark dataset available for irony detection for machine learning models. Ciron includes more than 8.7K posts, collected from Weibo, a micro blogging platform. Most importantly, Ciron is collected with no pre-conditions to ensure a much wider coverage. Evaluation on seven different machine learning classifiers proves the usefulness of Ciron as an important resource for Chinese irony detection.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: Proceedings of the 12th Language Resources and Evaluation Conference
Uncontrolled Keywords: Irony detection; Chinese benchmark dataset; social media text; text processing
Divisions: Faculty of Science and Health
Faculty of Science and Health > Computer Science and Electronic Engineering, School of
SWORD Depositor: Elements
Depositing User: Elements
Date Deposited: 03 Dec 2020 10:38
Last Modified: 17 Jan 2022 13:14

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