Multi-modal Public Opinion Analysis Based on Image and Text Fusion

Abstract

Due to the continuous popularization of the Internet and mobile phones, people have gradually entered a participatory network era. More and more people like to publish their opinions, comments and emotions through text and image on the Internet. Effective analysis of these text and image information can not only help companies better improve the quality of their products, but also provide guidance for government decision-making and social production and life. This paper summarizes the sentiment analysis of online public opinion based on multi-modal image and text fusion. Firstly, it summarizes the basic concepts of public opinion analysis. Secondly, it explains the process of single-modal text and visual sentiment analysis on social media. Thirdly, it summarizes the public opinion analysis algorithms based on image and text fusion, and divides the algorithms into feature layer fusion, decision layer fusion and linear regression model according to different fusion strategies. In addition, it summarizes the commonly used multi-modal sentiment analysis for social media dataset. Finally, the difficulties of online opinion analysis and future research directions are discussed.

Keywords

• |network public opinion analysis|image and text fusion|sentiment analysis|multi-modal