A Survey on Event Tracking in Social Media Data Streams

作     者：Zixuan Han Leilei Shi Lu Liu Liang Jiang Jiawei Fang Fanyuan Lin Jinjuan Zhang John Panneerselvam Nick Antonopoulos 

作者机构：School of Computer Science and Communication Engineering and Jiangsu Key Laboratory of Security Technology for Industrial CyberspaceJiangsu UniversityZhenjiang 212013China School of Computing and Mathematical SciencesUniversity of LeicesterLeicesterLE17RHUK Ocean CollegeJiangsu University of Science and TechnologyZhenjiang 212100China University Executive OfficeEdinburgh Napier UniversityEdinburghEH114BNUK 

出 版 物：《Big Data Mining and Analytics》 (大数据挖掘与分析（英文）)

年 卷 期：2024年第7卷第1期

页      面：217-243页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：This work was supported by the National Natural Science Foundation of China(No.62302199) the China Postdoctoral Science Foundation(No.2023M731368) the Natural Science Foundation of the Jiangsu Higher Education Institutions(No.22KJB520016) the Jiangsu University Innovative Research Project(No.KYCX22_3671) the Youth Foundation Project of Humanities and Social Sciences of Ministry of Education in China(No.22YJC870007) the Jiangsu University Undergraduate Student English Teaching Excellence Program,and the Ministry of Education's Industry-Education Cooperation Collaborative Education Project(No.202102306005) 

主　　题：Event Detection(ED) event propagation event evolution social networks 

摘      要：Social networks are inevitable parts of our daily life,where an unprecedented amount of complex data corresponding to a diverse range of applications are *** such,it is imperative to conduct research on social events and patterns from the perspectives of conventional sociology to optimize services that originate from social *** tracking in social networks finds various applications,such as network security and societal governance,which involves analyzing data generated by user groups on social networks in real ***,as deep learning techniques continue to advance and make important breakthroughs in various fields,researchers are using this technology to progressively optimize the effectiveness of Event Detection(ED)and tracking *** this regard,this paper presents an in-depth comprehensive review of the concept and methods involved in ED and tracking in social *** introduce mainstream event tracking methods,which involve three primary technical steps:ED,event propagation,and event ***,we introduce benchmark datasets and evaluation metrics for ED and tracking,which allow comparative analysis on the performance of mainstream ***,we present a comprehensive analysis of the main research findings and existing limitations in this field,as well as future research prospects and challenges.