摘要
[目的/意义]互联网环境下,移动社交媒体中的图像文字等多模态用户生成内容(UGC)已成为影响用户决策的重要信息类型。关于其用户信息采纳的研究大多将图文等多模态内容割裂看待,导致UGC的多维特征,尤其是融合特征,对用户信息采纳的综合影响机制尚不清晰。[方法/过程]文章选取小红书这一代表性的经验分享型移动社交媒体作为研究对象,利用自然语言处理与机器视觉技术对信息分析方法进行改进,提出覆盖图文深层、浅层以及融合特征的多模态UGC多维特征测度方法,并进一步构建多维特征对用户信息采纳的影响机制计量模型。[结果/结论]研究发现,两种图文协调性特征对于用户信息采纳的影响力显著高于单独的图像或文字特征;图文浅层特征比深层特征的影响力更大;影响用户信息采纳的各关键特征之间存在调节作用;自然、物体和其他这三类场景中的具体影响机制存在异质性。研究对于促进移动社交媒体中高质量的UGC创作和有效的信息采纳具有重要参考价值。
[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-making.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 multidimensional 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 improve the information analysis method by utilizing NLP and CV technologies.Specifically,we propose a multidimensional feature measurement method for multimodal UGC,which captures both images and text's deep,shallow,and fusion features.Furthermore,we develop an econometric model to investigate the influence mechanism of multidimensional features on user information adoption.[Result/conclusion]The results indicate that the impact of two image-textharmony features on user information adoption is significantly higher than that of image or text features in isolation.Additionally,the influence of shallow features is greater than that of deep features;the key features affecting user information 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.
作者
傅予
曹屹楠
王强
Fu Yu;Cao Yi′nan;Wang Qiang(School of Information Resource Management,Renmin University of China,Beijing,100872;School of Economics and Management,Beihang University,Beijing,100191)
出处
《情报资料工作》
北大核心
2024年第1期55-67,共13页
Information and Documentation Services
基金
国家自然科学基金项目“基于计算社会科学范式的旅游舆情自动内容分析方法与应用研究:以旅游危机沟通为例”(批准号:72004224)的研究成果之一。
关键词
移动社交媒体
多模态用户生成内容
信息分析方法
多维特征融合
信息采纳
mobile social media
multimodal user generated content
information analysis methods
multidimensional feature fusion
information adoption
