Optimal Social Influence

  • Wen Xu
  • Weili Wu

Part of the SpringerBriefs in Optimization book series (BRIEFSOPTI)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Wen Xu, Weili Wu
    Pages 1-20
  3. Wen Xu, Weili Wu
    Pages 21-36
  4. Wen Xu, Weili Wu
    Pages 65-91
  5. Back Matter
    Pages 115-124

About this book


This self-contained book describes social influence from a computational point of view, with a focus on recent and practical applications, models, algorithms and open topics for future research. Researchers, scholars, postgraduates and developers interested in research on social networking and the social influence related issues will find this book useful and motivating. The latest research on social computing is presented along with and illustrations on how to understand and manipulate social influence for knowledge discovery by applying various data mining techniques in real world scenarios. Experimental reports, survey papers, models and algorithms with specific optimization problems are depicted. The main topics covered in this book are: chrematistics of social networks, modeling of social influence propagation, popular research problems in social influence analysis such as influence maximization, rumor blocking, rumor source detection, and multiple social influence competing.  


modeling of social influence social networks Social computing social network mining rumor blocking rumor source detection multiple influence competing user behavior prediction social influence propagation social networks optimization algorithms

Authors and affiliations

  • Wen Xu
    • 1
  • Weili Wu
    • 2
  1. 1.Department of Mathematics and Computer ScienceTexas Woman’s UniversityDentonUSA
  2. 2.Department of Computer ScienceUniversity of Texas, DallasRichardsonUSA

Bibliographic information

  • DOI
  • Copyright Information The Author(s), under exclusive license to Springer Nature Switzerland AG 2020
  • Publisher Name Springer, Cham
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-030-37774-8
  • Online ISBN 978-3-030-37775-5
  • Series Print ISSN 2190-8354
  • Series Online ISSN 2191-575X
  • Buy this book on publisher's site