End user searching on the Internet: An analysis of term pair topics submitted to the Excite search engine

• Published in: Journal of the American Society for Information Science Vol. 51; no. 10; pp. 949 - 958
• Main Authors: Ross, Nancy C. M., Wolfram, Dietmar
• Format: Journal Article
• Language: English
• Published: New York John Wiley & Sons, Inc 01.08.2000; John Wiley & Sons; American Documentation Institute; Wiley Periodicals Inc
• Subjects: Bibliometrics. Scientometrics. Evaluation; Boolean; Cluster Analysis; Cocitation; Cooccurrence (Grammar); Datasets; End users; Exact sciences and technology; Excite; Indexing; Information and communication sciences; Information processing and retrieval; Information professionals; Information retrieval; Information retrieval. Man machine relationship; Information science. Documentation; Informetrics; Internet; Library and information science; Library and information science. General aspects; Library science; Multidimensional Scaling; Online information retrieval; Online Searching; Queries; Query expansion; Query formulation; Query Processing; Scaling; Sciences and techniques of general use; Search Engines; Search Strategies; Searching; Simulation; Studies; Subject Index Terms; Term Matching; Term pairs; Topics; Users (Information); United States > US; Cluster analysis; Research field; Query; Informetrics; Search engine; Information retrieval; Internet; Cooccurrence analysis; Content analysis
• ISSN: 0002-8231; 2330-1635; 1097-4571; 2330-1643
• DOI: 10.1002/1097-4571(2000)51:10<949::AID-ASI70>3.0.CO;2-5

Queries submitted to the Excite search engine were analyzed for subject content based on the cooccurrence of terms within multiterm queries. More than 1000 of the most frequently cooccurring term pairs were categorized into one or more of 30 developed subject areas. Subject area frequencies and their cooccurrences with one another were tallied and analyzed using hierarchical cluster analysis and multidimensional scaling. The cluster analyses revealed several anticipated and a few unanticipated groupings of subjects, resulting in several well‐defined high‐level clusters of broad subject areas. Multidimensional scaling of subject cooccurrences revealed similar relationships among the different subject categories. Applications that arise from a better understanding of the topics users search and their relationships are discussed.