Deakin University

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Overview of influence maximization in social media data analytics

conference contribution
posted on 2017-01-01, 00:00 authored by Jianxin LiJianxin Li
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.



World Wide Web Conferences Steering Committee. International Conference (26th : 2017 : Perth, W. A).


1201 - 1201




Perth, W. A.

Place of publication

New York, N.Y.

Start date


End date






Publication classification

E1.1 Full written paper - refereed

Copyright notice

2017, Republic and Canton of Geneva, Switzerland

Title of proceedings

WWW '17 Companion : Proceedings of the 26th International Conference on World Wide Web Companion