基于图文融合的多模态舆情分析

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

由于互联网以及移动手机的不断普及,人们逐渐进入到一个参与式的网络时代,越来越多的人们喜欢在网络上通过文本和图像的方式发布自己的观点、评论以及情感。对于这些文本和图像信息进行有效分析,不仅可以帮助企业更好地提高产品的质量,而且有利于为政府决策和社会生产生活提供指导。对基于多模态图文融合的网络舆情情感分析进行了综述。首先对舆情分析的基本概念进行了概括;其次对社交媒体上单模态的文本和视觉舆情情感分析的过程进行了说明;然后对基于图文融合的舆情分析算法进行了总结,并按照不同融合策略,将其分为特征层融合、决策层融合和线性回归模型;另外总结了针对社交媒体的多模态情感分析的常用数据集;最后讨论了网络舆情分析的难点以及未来研究方向。

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.