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Thelwall, Mike – Internet Research, 2002
Describes Web survey methodologies used to study the content of the Web, and discusses search engines and the concept of crawling the Web. Highlights include Web page selection methodologies; obstacles to reliable automatic indexing of Web sites; publicly indexable pages; crawling parameters; and tests for file duplication. (Contains 62…
Descriptors: Content Analysis, Indexing, Measurement Techniques, Search Engines

Thelwall, Mike; Wilkinson, David – Journal of the American Society for Information Science and Technology, 2003
Explains how the Web can be modeled as a mathematical graph and analyzes the graph structures of three national university publicly indexable Web sites from Australia, New Zealand, and the United Kingdom. Topics include commercial search engines and academic Web link research; method-analysis environment and data sets; and power laws. (LRW)
Descriptors: Foreign Countries, Graphs, Higher Education, Search Engines

Thelwall, Mike – Online Information Review, 2002
Discusses subject gateway sites and commercial search engines for the Web and presents an explanation of Google's PageRank algorithm. The principle question addressed is the conditions under which a gateway site will increase the likelihood that a target page is found in search engines. (LRW)
Descriptors: Algorithms, Gateway Systems, Search Engines, Search Strategies
Tang, Rong; Thelwall, Mike – Proceedings of the ASIST Annual Meeting, 2002
Compares links between 76 Chinese university Web sites with ranks obtained from the NetBig lists, using a specialized Web crawler to collect data. Provides a background to the higher education system in mainland China, describes the NetBig ranking scheme, and explains Web site crawling problems encountered. (Author/LRW)
Descriptors: Comparative Analysis, Foreign Countries, Higher Education, Search Engines
Thelwall, Mike – Proceedings of the ASIST Annual Meeting, 2001
Provides an up-to-date survey of the capabilities of the major 16 search engines with respect to the types of information extraction tasks that would be useful in Web data mining and cybermetrics, and analyzes two sets of domain counts for internal consistency between results. (AEF)
Descriptors: Comparative Analysis, Information Retrieval, Information Seeking, Online Searching