Bloggers Behavior and Emergent Communities in Blog Space

TL;DR

This paper analyzes user interactions and community formation in blog spaces using bipartite graph analysis, revealing temporal activity patterns and interest-based user clusters, with implications for modeling cyber communities and content retrieval.

Contribution

It introduces a spectral method approach to detect user communities in blog networks and explores mechanisms behind popular blog dynamics.

Findings

Identified temporal patterns of user-blog interactions.

Detected user clusters based on interests and habits.

Suggested different mechanisms for popular blogs.

Abstract

Interactions between users in cyberspace may lead to phenomena different from those observed in common social networks. Here we analyse large data sets about users and Blogs which they write and comment, mapped onto a bipartite graph. In such enlarged Blog space we trace user activity over time, which results in robust temporal patterns of user--Blog behavior and the emergence of communities. With the spectral methods applied to the projection on weighted user network we detect clusters of users related to their common interests and habits. Our results suggest that different mechanisms may play the role in the case of very popular Blogs. Our analysis makes a suitable basis for theoretical modeling of the evolution of cyber communities and for practical study of the data, in particular for an efficient search of interesting Blog clusters and further retrieval of their contents by text analysis.