Dewey Class |
515.353 |
Title |
Modeling Information Diffusion in Online Social Networks with Partial Differential Equations ([EBook]) / by Haiyan Wang, Feng Wang, Kuai Xu. |
Author |
Wang, Haiyan |
Added Personal Name |
Wang, Feng |
Xu, Kuai |
Other name(s) |
SpringerLink (Online service) |
Edition statement |
1st ed. 2020. |
Publication |
Cham : : Springer International Publishing : : Imprint: Springer, , 2020. |
Physical Details |
XIII, 144 p. 39 illus., 29 illus. in color. : online resource. |
Series |
Surveys and Tutorials in the Applied Mathematical Sciences 2199-4765 ; ; 7 |
ISBN |
9783030388522 |
Summary Note |
The book lies at the interface of mathematics, social media analysis, and data science. Its authors aim to introduce a new dynamic modeling approach to the use of partial differential equations for describing information diffusion over online social networks. The eigenvalues and eigenvectors of the Laplacian matrix for the underlying social network are used to find communities (clusters) of online users. Once these clusters are embedded in a Euclidean space, the mathematical models, which are reaction-diffusion equations, are developed based on intuitive social distances between clusters within the Euclidean space. The models are validated with data from major social media such as Twitter. In addition, mathematical analysis of these models is applied, revealing insights into information flow on social media. Two applications with geocoded Twitter data are included in the book: one describing the social movement in Twitter during the Egyptian revolution in 2011 and another predicting influenza prevalence. The new approach advocates a paradigm shift for modeling information diffusion in online social networks and lays the theoretical groundwork for many spatio-temporal modeling problems in the big-data era.: |
Contents note |
Ordinary Differential Equation Models on Social Networks -- Spatio-temporal Patterns of Information Diffusion -- Clustering of Online Social Network Graphs -- Partial Differential Equation Models -- Modeling Complex Interactions -- Mathematical Analysis -- Applications. |
Mode of acces to digital resource |
Digital book. Cham Springer Nature 2020. - Mode of access: World Wide Web. System requirements: Internet Explorer 6.0 (or higher) or Firefox 2.0 (or higher). Available as searchable text in PDF format |
System details note |
- Online access to this digital book is restricted to subscription institutions through IP address (only for SISSA internal users). |
Internet Site |
https://doi.org/10.1007/978-3-030-38852-2 |
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