Journal of Data Mining and Knowledge Discovery Special Issue Call for Papers

 

Data Mining Technologies for Computational Social Science

 

Social Science has long been used as an umbrella term to refer to a plurality of fields outside natural sciences, such as economics, linguistics, education and even psychology.  It can be any discipline or branch of science that deals with the sociocultural aspects of human behavior. There are many fundamental problems in social sciences, such as detecting underlying communities, analyzing the mechanism of a specific behavior/social activity and discovering the evolutionary patterns in a community. The emergence of online social network sites and web 2.0 applications generate a large volume of valuable data. This greatly stimulates the development of computational social science, which tries to solve the research problems in traditional social science with the help of computational technologies.

 

In recent years, the computing technologies, such as data mining, machine learning and statistics, has been developing rapidly. More and more sophisticated methods, such as Support Vector Machine, Matrix and Graph based models, Probabilistic Networks, and Parallel Computation, have been proposed and many of them have already been deployed in the analysis of social sciences. The major goal of this special issue is to bring together the researchers in computational social sciences to illustrate pressing needs, demonstrate challenging research issues, and showcase the state-of-the-art research and development.

 

Topic of Interests

 

The topics of this special issue include, but not limit to, the following:

 

·         Graph and matrix methods for computational social science

·         Probabilistic models for computational social science

·         Tensor models for evolving social network analysis

·         Transfer learning on heterogeneous networks

·         Scalable social network analysis

·         Link analysis and network structure discovery

·         Viral marketing and influence propagation

·         User behavior modeling

·         Social tagging, blog and forum analysis

·         Security and Privacy in computational social science

·         Query log and click through data analysis

·         Expertise and authority discovery

·         Social navigation and visualization

·         Collaborative filtering and recommendation      

 

Submission Guidelines

 

Manuscripts should be submitted to http://www.editorialmanager.com/dami/default.asp by selecting article type “SI: DM Technologies for Comp. Social Sci”.

 

Planned Timeline

 

May 1, 2011:    Paper Submission Due

Sep. 1, 2011:    Author Notification after first round review

Oct. 1, 2011:     Revision Due

Nov. 1, 2011:    Author Notification after second round of review

Dec. 1, 2011:    Camera-Ready Due

 

Special Issue Guest Editors

 

 

Download the official CFP