A survey on information diffusion in social media

PhD Qualifying Examination


Title: "A survey on information diffusion in social media"

by

Mr. Conglei Shi


Abstract:

The diffusion of innovation, known as the spread of new ideas or products 
through certain channels, has been heavily studied in a variety of areas 
such as marketing, economy, finance, and public health. Recently, the 
development of the Internet technology offers people a new platform to 
acquire the information, express their opinions, and communicate with each 
other. The social media such as blogs, Twitter, and Facebook has become a 
very important diffusion channel for ideas and products. People have 
proposed many data processing and mining techniques in recent years to 
study information diffusion in social media.  However, there is limited 
research on visualization of information diffusion which can help people 
detect unexpected patterns, present mining results in intuitive ways, and 
convey findings to a wider range of audience.

In this survey, I first introduce the diffusion of innovation theory and 
related applications. Then some major data processing and analysis 
techniques for social media such as topic extraction, topology 
construction, and sentiment analysis are reviewed. After describing 
several widely used diffusion models, I present three research problems 
related to information diffusion in social media (i.e., influence 
maximization, community detection, and link prediction) and review major 
data mining methods for each problem. Next, some relevant visualization 
techniques such as social network visualization and flow visualization are 
summarized. Finally, I point out some research directions for visual 
analysis of information diffusion in social media.


Date:                   Tuesday, 4 October 2011

Time:                   3:00pm - 5:00pm

Venue:                  Room 3408
                         lifts 17/18

Committee Members:	Dr. Huamin Qu (Supervisor)
                         Prof. Qiang Yang (Chairperson)
 			Prof. Long Quan
 			Prof. Chi-Keung Tang


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