Shi Li, Didi Sun*
CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1069-1086, 2025, DOI:10.32604/cmc.2024.057349
- 03 January 2025
Abstract With the rapid expansion of social media, analyzing emotions and their causes in texts has gained significant importance. Emotion-cause pair extraction enables the identification of causal relationships between emotions and their triggers within a text, facilitating a deeper understanding of expressed sentiments and their underlying reasons. This comprehension is crucial for making informed strategic decisions in various business and societal contexts. However, recent research approaches employing multi-task learning frameworks for modeling often face challenges such as the inability to simultaneously model extracted features and their interactions, or inconsistencies in label prediction between emotion-cause pair extraction… More >
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