【学术报告】Analyzing Information Diffusion Process over Social Networks

发稿时间:2009-11-01浏览次数:1671

题目:
Analyzing Information Diffusion Process over Social Networks

报告人:
Hiroshi Motoda
Osaka University and AFOSR/AOARD, Japan

时间:
11月5日(星期四) 下午2:00-4:00

地点:
蒙民伟楼404会议室

摘要:
The rise of the Internet and the World Wide Web accelerates the creation of
various large-scale social networks, where nodes (vertices) correspond to
people or some social entities, and links (edges) correspond to social
interaction between them. Clearly these social networks reflect complex social
structures and distributed social trends. A social network can also play an
important role as a medium for the spread of various types of information in
the form of so-called ``word-of-mouth'' communications. For example,
innovation, hot topics and even malicious rumors can propagate through social
networks, and computer viruses can diffuse through email networks. Widely-used
information diffusion models are not deterministic but probabilistic. 
Because of this probabilistic nature, influence of a node over a network is
defined in terms of its expectation (average number of nodes it influences).
Thus, analyzing how information diffuses over social networks involves heavy
computation. I first show that a typical social network is different from a
random network and address the difficulty associated with the information
diffusion problem. Then I explain the networks (blog and Wikipedia) and the
information diffusion models (independent cascade, linear threshold and their
variants) we used for our analyses.

简历:
Hiroshi Motoda is scientific advisor of AFOSR/AOARD (Asian Office of Aerospace
Research and Development, Air Force Office of Scientific Research, US Air
Force Research Laboratory) and professor emeritus of Osaka University, guest
professor of the Institute of Scientific and Industrial Research of Osaka
University, and visiting professor of the school of computing of University of
New South Wales.