Research on Text Micro Emotion Analysis Based on Multitasking and Self Attention Mechanism
YANG Jianhao
ZENG Biqing
DENG Huimin
PEI Fenghua
YAO Bowen
Abstract：The research on text micro emotion analysis based on multitasking and self attention mechanism aims to mine the emotions involved in sentences(4 classification,7 classification and 28 classification),especially the micro emotions of sentences in 28 classification.Most of the existing literature still focuses on coarse-grained(4 classification)emotion research.However,there is little research on micro emotion of 7 categories,especially 28 categories.In order to solve the above problems and make up for the gap in the domestic research on micro emotion(28 classification),this paper proposes a micro emotion analysis model based on multi task and self attention mechanism,that is,through the simultaneous processing of three emotion analysis tasks of 4 classifi-cation,7 classification and 28 classification,one of them is the main task(with a weight of 0.9).The other two tasks are used as auxiliary tasks(with a weight of 0.05 respectively)and share the network weight of the three tasks to achieve the goal of improving the main task model.Experiments show that the network sharing of coding layer for multiple tasks with different granularity can im-prove the text feature extraction ability of the model for sentences,so as to improve the emotion recognition accuracy of the model for sentences,especially in fine-grained(micro)emotion classification tasks.
Keywords：multitaskingmicro emotionnatural language processingBERT
Publication Date：2023-12-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 2863-2866,3009 )