Exploring Trends and Patterns of Popularity Stage Evolution in Social Media
Qingchao Kong; Wenji Mao; Guandan Chen; Daniel Zeng
Source PublicationIEEE Transactions on Systems, Man, and Cybernetics: Systems
ISSN2168-2216
2018
Volume50Issue:0Pages:1-11
Corresponding AuthorMao, Wenji(wenji.mao@ia.ac.cn)
AbstractThe popularity of online contents in social media frequently experiences ebb and flow, and thus its evolution often involves different stages, such as burst and valley. Exploring the patterns of popularity evolution, especially how burst forms and decays, and even further, predicting the trends of popularity evolution is both an important research topic and beneficial to support decision making for many applications, such as emergency management, business intelligence, and public security. Previous work on popularity prediction has focused on predicting the popularity volume of online contents, and at most, popularity burst and ignored the exploration of popularity evolution and the prediction of its stages. To fill this gap, in this paper, we propose our method for the popularity stage prediction problem both at the microscopic level and macroscopic level. At the microscopic level, we first extract multiple dynamic factors and infer future evolution stage by considering the contributions of different dynamic factors. At the macroscopic level, we extract the overall evolution patterns of popularity stages and adopt a pattern matching-based method to predict future popularity stages. We evaluate the proposed approach using tweets in SinaWeibo, the most popular Twitter-like social media platform in China. The experimental results show the effectiveness of our proposed approach in predicting popularity evolution stages.
Other Abstract
KeywordOnline Contents Popularity Evolution Popularity Stage Prediction (Psp) Social Media Analytics
DOI10.1109/TSMC.2018.2855806
WOS KeywordPREDICTION ; DIFFUSION
Indexed BySCI
Language英语
Funding ProjectMinistry of Science and Technology of China[2016QY02D0305] ; National Natural Science Foundation of China[71702181] ; National Natural Science Foundation of China[71621002] ; Key Program of the Chinese Academy of Sciences[ZDRW-XH-2017-3]
Funding OrganizationMinistry of Science and Technology of China ; National Natural Science Foundation of China ; Key Program of the Chinese Academy of Sciences
WOS Research AreaAutomation & Control Systems ; Computer Science
WOS SubjectAutomation & Control Systems ; Computer Science, Cybernetics
WOS IDWOS:000571736100029
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/21797
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
Corresponding AuthorWenji Mao
Affiliation1.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
2.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
3.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
4.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Qingchao Kong,Wenji Mao,Guandan Chen,et al. Exploring Trends and Patterns of Popularity Stage Evolution in Social Media[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems,2018,50(0):1-11.
APA Qingchao Kong,Wenji Mao,Guandan Chen,&Daniel Zeng.(2018).Exploring Trends and Patterns of Popularity Stage Evolution in Social Media.IEEE Transactions on Systems, Man, and Cybernetics: Systems,50(0),1-11.
MLA Qingchao Kong,et al."Exploring Trends and Patterns of Popularity Stage Evolution in Social Media".IEEE Transactions on Systems, Man, and Cybernetics: Systems 50.0(2018):1-11.
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