Mapping Blog Communities with Self-Organizing Maps

Title: Mapping Blog Communities with Self-Organizing Maps

Research Question: How can we visualize and understand the complex network of blog communities using self-organizing maps (SOMs)?

Methodology: The researchers used Kohonen's self-organizing map (SOM), a neural-network-like method commonly used for clustering and visualizing complex data sets. They applied this method to a network of blogs hosted on the Blogalia website, which had around 200 members.

Results: The SOM revealed interesting features of the blog community, such as the presence of subcommunities and the relationships between different bloggers. It also highlighted the hierarchical structure within the community and the evolution of the blog network over time.

Implications: This study suggests that SOMs can be a useful tool for mapping and understanding complex blog communities. By visualizing the relationships between blogs, it can help identify key influencers, reveal hidden subcommunities, and track the evolution of the community. This has implications for researchers studying online communities, as well as for bloggers and website owners who want to understand their position within the blogosphere.

Link to Article: https://arxiv.org/abs/0312047v1 Authors: arXiv ID: 0312047v1