Springer Book Archives: eBooks only 8.99 each! Save now >>

Surveys and Tutorials in the Applied Mathematical Sciences

Modeling Information Diffusion in Online Social Networks with Partial Differential Equations

Authors: Wang, Haiyan, Wang, Feng, Xu, Kuai

Free Preview
  • ​Provides a new and timely modeling approach for information diffusion in social media
  • Written by the experts who initiated the approach of modeling with partial differential equations (PDEs)
  • Accessible to a wide range of readers in mathematics, computer science, and social media
  • Presents models which have been validated with real datasets from popular social media sites
see more benefits

Buy this book

eBook 49,99 €
price for Spain (gross)
  • ISBN 978-3-030-38852-2
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 62,39 €
price for Spain (gross)
  • ISBN 978-3-030-38850-8
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

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.

Table of contents (8 chapters)

Table of contents (8 chapters)

Buy this book

eBook 49,99 €
price for Spain (gross)
  • ISBN 978-3-030-38852-2
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 62,39 €
price for Spain (gross)
  • ISBN 978-3-030-38850-8
  • Free shipping for individuals worldwide
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
  • The final prices may differ from the prices shown due to specifics of VAT rules
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Modeling Information Diffusion in Online Social Networks with Partial Differential Equations
Authors
Series Title
Surveys and Tutorials in the Applied Mathematical Sciences
Series Volume
7
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-38852-2
DOI
10.1007/978-3-030-38852-2
Softcover ISBN
978-3-030-38850-8
Series ISSN
2199-4765
Edition Number
1
Number of Pages
XIII, 144
Number of Illustrations
10 b/w illustrations, 29 illustrations in colour
Topics

*immediately available upon purchase as print book shipments may be delayed due to the COVID-19 crisis. ebook access is temporary and does not include ownership of the ebook. Only valid for books with an ebook version. Springer Reference Works are not included.