Abstract
Sarcasm is a commonly-used language phenomenon particularly on the Internet, which is often to convey criticism or negative emotions. A proper sarcasm corpus to help sarcasm study and detection can contribute to linguistic research and assist sentiment analysis, but an open Chinese corpus is found extremely lacking. In this paper, we referenced existing methods and data and constructed a balanced open Chinese Internet sarcasm corpus in a new approach to improve efficiency and data quality. The balanced open corpus contains multi-source and labeled 2,000 texts selected from bigger corresponding origin datasets. In our corpus, sarcasm and non-sarcasm, longer and shorter texts are both in 1:1 ratio.
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