Haiyan Wang

Kuai Xu

Feng Wang

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.

Modeling Information Diffusion in Online Social Networks with Partial Differential Equations

Haojin Zhu

This book constitutes the proceedings of the 10th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2015, held in Qufu, Shandong, China, in August 2015. The 36 revised full papers presented together with 5 revised short papers and 42 invited papers were carefully reviewed and selected from 133 initial submissions. The papers present current trends, challenges, and state-of-the-art solutions related to various issues in wireless networks. Topics of interests include effective and efficient state-of-the-art algorithm design and analysis, reliable and secure system development and implementations, experimental study and testbed validation, and new application exploration in wireless networks. .

Kuai Xu

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