Modeling Information Diffusion In Online Social Networks With Partial Differential Equations

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Modeling Information Diffusion in Online Social Networks with Partial Differential Equations

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.
Information Diffusion Management and Knowledge Sharing: Breakthroughs in Research and Practice

Author: Management Association, Information Resources
language: en
Publisher: IGI Global
Release Date: 2019-10-11
Within the past 10 years, tremendous innovations have been brought forth in information diffusion and management. Such technologies as social media have transformed the way that information is disseminated and used, making it critical to understand its distribution through these mediums. With the consistent creation and wide availability of information, it has become imperative to remain updated on the latest trends and applications in this field. Information Diffusion Management and Knowledge Sharing: Breakthroughs in Research and Practice examines the trends, models, challenges, issues, and strategies of information diffusion and management from a global context. Highlighting a range of topics such as influence maximization, information spread control, and social influence, this publication is an ideal reference source for managers, librarians, information systems specialists, professionals, researchers, and administrators seeking current research on the theories and applications of global information management.
Intelligent Information and Database Systems

The two-volume set LNAI 10751 and 10752 constitutes the refereed proceedings of the 10th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2018, held in Dong Hoi City, Vietnam, in March 2018. The total of 133 full papers accepted for publication in these proceedings was carefully reviewed and selected from 423 submissions. They were organized in topical sections named: Knowledge Engineering and Semantic Web; Social Networks and Recommender Systems; Text Processing and Information Retrieval; Machine Learning and Data Mining; Decision Support and Control Systems; Computer Vision Techniques; Advanced Data Mining Techniques and Applications; Multiple Model Approach to Machine Learning; Sensor Networks and Internet of Things; Intelligent Information Systems; Data Structures Modeling for Knowledge Representation; Modeling, Storing, and Querying of Graph Data; Data Science and Computational Intelligence; Design Thinking Based R&D, Development Technique, and Project Based Learning; Intelligent and Contextual Systems; Intelligent Systems and Algorithms in Information Sciences; Intelligent Applications of Internet of Thing and Data Analysis Technologies; Intelligent Systems and Methods in Biomedicine; Intelligent Biomarkers of Neurodegenerative Processes in Brain; Analysis of Image, Video and Motion Data in Life Sciences; Computational Imaging and Vision; Computer Vision and Robotics; Intelligent Computer Vision Systems and Applications; Intelligent Systems for Optimization of Logistics and Industrial Applications.