Online Social Media Content Delivery A Data-Driven Approach /

• Main Authors: Wang, Zhi (Author, http://id.loc.gov/vocabulary/relators/aut), Zhu, Wenwu (http://id.loc.gov/vocabulary/relators/aut), Yang, Shiqiang (http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Singapore : Springer Singapore : Imprint: Springer, 2018.
• Edition: 1st ed. 2018.
• Series: SpringerBriefs in Computer Science,
• Subjects: Application software.; Artificial intelligence.; Information Systems Applications (incl. Internet).; Artificial Intelligence.; Computer Appl. in Social and Behavioral Sciences.
• Physical Description: XI, 109 p. 64 illus. online resource.
• ISBN: 9789811027741
• ISSN: 2191-5768
• DOI: 10.1007/978-981-10-2774-1

This book explains how to use a data-driven approach to design strategies for social media content delivery. It first introduces readers to how social information can be effectively gathered for big data analysis, which provides content delivery intelligence. Secondly, the book describes data-driven models to capture information diffusion in online social networks and social media content propagation and popularity, before presenting prediction models for social media content delivery. By addressing the resource allocation and content replication aspects of social media content delivery, the book presents the latest data-driven strategies. In closing, it outlines a number of potential research directions regarding social media content delivery.