CFN: A Complex-Valued Fuzzy Network for Sarcasm Detection in Conversations

Sarcasm detection in conversation, a theoretically and practically challenging artificial intelligence task, aims to discover elusively ironic, contemptuous, metaphoric information implied daily conversations. Most of the recent approaches sarcasm have neglected intrinsic vagueness uncertainty human language emotional expression understanding. To address this gap, we propose complex-valued fuzzy network by leveraging mathematical formalisms quantum theory logic. In particular, target utterance be recognized is considered as superposition set separate words. The contextual interaction between adjacent utterances described system its surrounding environment, constructing composite system, where weight determined membership function. order model both uncertainty, aforementioned systems are mathematically encapsulated density matrix. Finally, measurement performed on matrix each yield probabilistic outcomes recognition. Extensive experiments conducted MUStARD 2020 Reddit track datasets, results show that our outperforms wide range strong baselines.