Information Propagation Formalized Representation of Micro-blog Network Based on Petri Nets

Author:

Liang Xun,Zhang ShusenORCID,Liu Yu,Ma Yuefeng

Abstract

AbstractThe description of user behavior in social networks is an important issue for studying social networks. Given that Petri nets can describe the resource flow problem, this study utilizes the features of Petri nets to portray the user behavior states during the message propagation of a micro-blog network and presents an information propagation formalized representation method of a micro-blog network. On this basis, this study analyzed the proposed formalized representation method in detail. We provide examples of applying formalized representation (e.g., micro-blog network addiction of users, user behavior influence, and public opinion analysis). In addition, we introduce the algorithms of formalized representation. We conduct experiments using Sina micro-blog data. Results show that the information propagation formalized representation method of micro-blog network based on Petri nets can depict user behaviors of micro-blog network intuitively and accurately. This study reveals a new perspective for information transmission of a micro-blog network and provides some tools to support public opinion monitoring and micro-blog marketing applications.

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on Social Network Marketing Strategy Based on Apriori Algorithm;2024 Asia-Pacific Conference on Software Engineering, Social Network Analysis and Intelligent Computing (SSAIC);2024-01-10

2. A Network Public Opinion Trend Estimation Model Using a Scale-Free Network Algorithm;Mobile Information Systems;2022-06-03

3. A CPN-based information propagation model in Online Social Networks;2021 20th International Conference on Ubiquitous Computing and Communications (IUCC/CIT/DSCI/SmartCNS);2021-12

4. Quantitative predicting propagation breadth and depth of microblog users’ forwarding behavior;Intelligent Data Analysis;2021-07-09

5. Modeling and analyzing a public opinion influence method with K-adaboost;International Journal of Modern Physics B;2020-10-27

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