软件导刊2019，Vol.18Issue(1)：9-13,16,6.DOI:10.11907/rjdk.181783
一种基于图文融合的跨模态社交媒体情感分析方法
A Cross-modal Social Media Sentiment Analysis Method Based on the Fusion of Image and Text
摘要
Abstract
Sentiment analysis is a hot field in artificial intelligence and social media research, which has a very important theoretical and practical value.In order to solve the problem of emotional mutual exclusion between texts and images caused by the randomness and emotional subjectivity of social media, a cross-modal social media sentiment analysis method based on the fusion of image and text is proposed.This method can not only learn the emotional complementarity between texts and images, but also avoid the problem of the inconsistency of emotional expression by introducing the modal contribution calculation.Experimental results on Veer and Weibo datasets show that this method is about 4％ more accurate than the existing fusion methods.The cross-modal social media sentiment analysis method based on the fusion of image and text can deal with the problem of modal mutual emotional exclusion well, and has strong recognition ability.关键词
社交媒体/情感分析/图文融合/贡献计算/跨模态Key words
social media/sentiment analysis/fusion of image and text/contribution calculation/cross-modal分类
信息技术与安全科学引用本文复制引用
申自强..一种基于图文融合的跨模态社交媒体情感分析方法[J].软件导刊,2019,18(1):9-13,16,6.基金项目
国家自然科学基金面上项目(61272211) （61272211）
