微博热度预测研究综述  

A Survey of Research on Microblog Popularity Prediction

作　　者：李妍 何洪波[1] 王闰强[1] LI Yan;HE Hongbo;WANG Runqiang(Computer Network Information Center,Chinese Academy of Sciences,Beijing 100083,China;University of Chinese Academy of Sciences,Beijing 100049,China)

机构地区：[1]中国科学院计算机网络信息中心,北京100083 [2]中国科学院大学,北京100049

出　　处：《数据与计算发展前沿》2023年第2期119-135,共17页Frontiers of Data & Computing

基　　金：中国科学院“十四五”网络安全和信息化专项子课题“网络空间科普云矩阵建设与应用”。

摘　　要：【目的】对现有微博热度预测研究展开多角度调研,讨论现有研究不足,展望未来发展趋势,为后续研究提供参考。【文献范围】本文整理和总结了近5年的国内外相关文献。【方法】本文首先介绍了热度预测问题的定义与热度计算方式,然后将热度预测研究方法从特征、时序和用户行为三个方面深入分析,再对热度预测问题的关键技术展开广泛调研,最后针对存在问题进行总结和展望。【结果】基于特征的热度预测方法因其定制性强被广泛使用,与深度学习和集成学习算法技术结合更是研究主流。【局限】由于各研究数据集未公开,本研究无法用统一的标准对所有算法技术的提升水平做横向对比。【结论】微博热度预测问题对于舆论监控、商业营销和内容推广等都具有一定意义,在社交媒体持续流行的时代,热度预测研究将会被继续深入推进。[Objective]This paper is to conduct a multi-angle survey of the existing research on microblog popularity prediction,discuss the shortcomings of the existing approaches,foresee the future development trend,and provide a reference for follow-on researches.[Coverage]The paper sorts out and summarizes relevant literatures both in China and abroad in recent five years.[Methods]The paper first introduces the definition of popularity prediction and popularity calculation methods.Then the research methods of popularity prediction are analyzed from three aspects:characteristics,time sequence,and user behavior.An extensive study is conducted on the key technologies of popularity prediction.Finally,the problems of the existing methods and the prospect are summarized.[Results]Feature-based popularity prediction methods are widely used because of they are well customized.The method combining deep learning and ensemble learning is becoming the mainstream approach.[Limitations]As the dataset of the individual research is not publicly available,this study cannot make a horizontal comparison of all algorithms for the level of improvement against a unified standard.[Conclusions]Microblog popularity prediction is significant for public opinion monitoring,commercial marketing,and content promotion,etc.In the era of ever-increasing popularity of social media,the research on popularity prediction will be further promoted.

关 键 词：热度预测 微博 机器学习 深度学习 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] G206[自动化与计算机技术—控制科学与工程]