Graph structure in three national academic Webs: Power laws with anomalies
- 16 April 2003
- journal article
- Published by Wiley in Journal of the American Society for Information Science and Technology
- Vol. 54 (8) , 706-712
- https://doi.org/10.1002/asi.10267
Abstract
The graph structures of three national university publicly indexable Webs from Australia, New Zealand, and the UK were analyzed. Strong scale‐free regularities for page indegrees, outdegrees, and connected component sizes were in evidence, resulting in power laws similar to those previously identified for individual university Web sites and for the AltaVista‐indexed Web. Anomalies were also discovered in most distributions and were tracked down to root causes. As a result, resource driven Web sites and automatically generated pages were identified as representing a significant break from the assumptions of previous power law models. It follows that attempts to track average Web linking behavior would benefit from using techniques to minimize or eliminate the impact of such anomalies.Keywords
This publication has 17 references indexed in Scilit:
- The top 100 linked-to pages on UK university web sites: high inlink counts are not usually associated with quality scholarly contentJournal of Information Science, 2002
- Methodologies for crawler based Web surveysInternet Research, 2002
- Winners don't take all: Characterizing the competition for links on the webProceedings of the National Academy of Sciences, 2002
- A web crawler design for data miningJournal of Information Science, 2001
- Bibliometrics and beyond: some thoughts on web-based citation analysisJournal of Information Science, 2001
- Extracting macroscopic information from Web linksJournal of the American Society for Information Science and Technology, 2001
- Graph structure in the WebComputer Networks, 2000
- Power-Law Distribution of the World Wide WebScience, 2000
- The calculation of web impact factorsJournal of Documentation, 1998
- A general theory of bibliometric and other cumulative advantage processesJournal of the American Society for Information Science, 1976