Web Community Discovery Using Personal Names

These days, web access is essential for our daily lives, and many communities are formed by the exchange of information. We propose a method for discovering web communities by using personal names. It extracts personal names fromsearch results that are relevant to a speci fic topic and finds appropriate web communities by analyzing the bipartite graph between personal names and websites. In general, web pages are too noisy to extract such social network structures automatically. We introduce a measure called effectiveness and extract only key people or key websites to make their bipartite graph. We also demonstrate an application called "Community Navigator" and visualize web communities for a specific topic by using it. Moreover, we analyze the measure for an actual example and show that it is suitable for selecting key people and key websites.