With the growth and widespread popularity of artificial intelligence (AI) and online media, online platforms have accumulated massive and diverse resources and data. Currently, multimodal data in social networks has become the mainstream form, and compared to traditional unimodal data, it contains richer and more comprehensive emotional features. Sentiment analysis (SA), also called viewpoint mining, aims to recognize and understand users' emotional tendencies, attitude evaluations, and subjective views expressed towards specific entities through computational means. It is an important technical means to improve the quality of network services and user experience. Conducting in-depth research on social platform data can not only optimize platform services, but also assist enterprises in precise marketing, conducting public opinion monitoring, and achieving personalized recommendations.
Gao Chien (Mon,) studied this question.