Different Approaches to Community Evolution Prediction in Blogosphere

Abstract

Predicting the future direction of community evolution is a problem with high theoretical and practical significance. It allows to determine which characteristics describing communities have importance from the point of view of their future behaviour. Knowledge about the probable future career of the community aids in the decision concerning investing in contact with members of a given community and carrying out actions to achieve a key position in it. It also allows to determine effective ways of forming opinions or to protect group participants against such activities. In the paper, a new approach to group identification and prediction of future events is presented together with the comparison to existing method. Performed experiments prove a high quality of prediction results. Comparison to previous studies shows that using many measures to describe the group profile, and in consequence as a classifier input, can improve predictions.

SNAA2013 at ASONAM2013 IEEE Computer Society

References in corpus (7)

• Estimating Continuous Distributions in Bayesian Classifiers
• The Slashdot Zoo: Mining a Social Network with Negative Edges
• GED: the method for group evolution discovery in social networks
• Predicting Positive and Negative Links in Online Social Networks
• Identification of Group Changes in Blogosphere
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Cited by in corpus (5)

• On community structure in complex networks: challenges and opportunities
• Predicting Community Evolution in Social Networks
• Analysis of group evolution prediction in complex networks
• Incorporating Text Analysis into Evolution of Social Groups in Blogosphere
• A Comparative Study of Different Approaches for Tracking Communities in Evolving Social Networks