Different Approaches to Community Evolution Prediction in Blogosphere

TL;DR

This paper introduces a new approach for predicting community evolution in the blogosphere, demonstrating that using multiple group profile measures enhances prediction accuracy.

Contribution

It presents a novel method for community identification and evolution prediction, comparing it with existing approaches and showing improved results.

Findings

High prediction quality demonstrated through experiments

Using multiple measures improves prediction accuracy

Comparison shows the new method outperforms previous approaches

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.