Research on the Influence Mechanism of Mobile Social Media User-Generated Content Information Adoption Based on Multidimensional Feature Fusion of Images and Texts
[Purpose/significance]In the Internet landscape,multimodal User-Generated Content(UGC)comprising images and text on mobile social media has emerged as a crucial information source influencing users'decision-mak-ing.However,existing studies on user information adoption have analyzed multimodal content such as images and text in a piecemeal fashion,leading to a lack of clarity regarding the comprehensive influence mechanism of multidimen-sional UGC features,especially fusion features,on user information adoption.[Method/process]This study employs Xiaohongshu,a representative experience-sharing mobile social media platform,as the research object.We further im-prove the information analysis method by utilizing NLP and CV technologies.Specifically,we propose a multidimen-sional feature measurement method for multimodal UGC,which captures both images and text's deep,shallow,and fu-sion features.Furthermore,we develop an econometric model to investigate the influence mechanism of multidimen-sional features on user information adoption.[Result/conclusion]The results indicate that the impact of two image-tex-tharmony features on user information adoption is significantly higher than that of image or text features in isolation.Ad-ditionally,the influence of shallow features is greater than that of deep features;the key features affecting user informa-tion adoption exhibit moderating effects;and the specific influence mechanisms differ in the three types of scenarios:nature,object,and others.The findings of this study provide crucial insights for facilitating high-quality UGC creation and effective information adoption in mobile social media.
mobile social mediamultimodal user generated contentinformation analysis methodsmultidimensional feature fusioninformation adoption
万方数据
维普
