Overview of influence maximization in social media data analytics

Li, Jianxin 2017, Overview of influence maximization in social media data analytics, in WWW '17 Companion : Proceedings of the 26th International Conference on World Wide Web Companion, ACM, New York, N.Y., pp. 1201-1201, doi: 10.1145/3041021.3053049.

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Title Overview of influence maximization in social media data analytics
Author(s) Li, JianxinORCID iD for Li, Jianxin orcid.org/0000-0002-9059-330X
Conference name World Wide Web Conferences Steering Committee. International Conference (26th : 2017 : Perth, W. A).
Conference location Perth, W. A.
Conference dates 2017/04/03 - 2017/04/07
Title of proceedings WWW '17 Companion : Proceedings of the 26th International Conference on World Wide Web Companion
Publication date 2017
Start page 1201
End page 1201
Total pages 1
Publisher ACM
Place of publication New York, N.Y.
Summary Social media has become a new and main platform for organizations to broadcast their policies, for companies to advertise their products, and for people to propagate their opinions. Therefore, social media data analytics has become a timely and significant research topic in recent years. In this talk, Dr. Li will first go through the social media background and the data representation of social media data. And then, he will briefly discuss the main stream research in social data mining and social computing. After that, Dr. Li will mainly introduce how the two most popular influence models are defined in social computing, what the influence maximization problem is defined, how its variants are defined. Finally, Dr. Li will introduce his current social media research project and discuss the interesting collaboration with attendees.This one-hour keynote targets researchers, designers and practitioners interested in social computing, social media data analytics, big data management systems and processing. While the audience with a good background in these areas would benefit most from this keynote, we believe the material to be presented would give general audience and newcomers an introductory pointer to the current work and important research topics in this field of viral marketing and social influence maximization, and inspire them to learn more. Only preliminary knowledge about graph, data mining, algorithms and their applications are needed.
ISBN 9781450349147
Language eng
DOI 10.1145/3041021.3053049
Indigenous content off
HERDC Research category E1.1 Full written paper - refereed
Copyright notice ©2017, Republic and Canton of Geneva, Switzerland
Persistent URL http://hdl.handle.net/10536/DRO/DU:30116199

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