The structure of broad topics on the web

The Web graph is a giant social network whose properties have been measured and modeled extensively in recent years. Most such studies concentrate on the graph structure alone, and do not consider textual properties of the nodes. Consequently, Web communities have been characterized purely in terms of graph structure and not on page content. We propose that a topic taxonomy such as Yahoo! or the Open Directory provides a useful framework for understanding the structure of content-based clusters and communities. In particular, using a topic taxonomy and an automatic classifier, we can measure the background distribution of broad topics on the Web, and analyze the capability of recent random walk algorithms to draw samples which follow such distributions. In addition, we can measure the probability that a page about one broad topic will link to another broad topic. Extending this experiment, we can measure how quickly topic context is lost while walking randomly on the Web graph. Estima...

• Type: Conference
• Year: 2002
• Where: WWW
• Authors: Soumen Chakrabarti, Mukul Joshi, Kunal Punera, David M. Pennock
• Keywords: Broad Topic, Internet Technology, Topic Mixing Distance, Topic Taxonomy, WWW 2002