Analysis of query keywords of sports‐related queries using visualization and clustering

Jin Zhang, Dietmar Wolfram and Peiling Wang

Journal of the American Society for Information Science and Technology, 2009, vol. 60, issue 8, 1550-1571

Abstract: The authors investigated 11 sports‐related query keywords extracted from a public search engine query log to better understand sports‐related information seeking on the Internet. After the query log contents were cleaned and query data were parsed, popular sports‐related keywords were identified, along with frequently co‐occurring query terms associated with the identified keywords. Relationships among each sports‐related focus keyword and its related keywords were characterized and grouped using multidimensional scaling (MDS) in combination with traditional hierarchical clustering methods. The two approaches were synthesized in a visual context by highlighting the results of the hierarchical clustering analysis in the visual MDS configuration. Important events, people, subjects, merchandise, and so on related to a sport were illustrated, and relationships among the sports were analyzed. A small‐scale comparative study of sports searches with and without term assistance was conducted. Searches that used search term assistance by relying on previous query term relationships outperformed the searches without the search term assistance. The findings of this study provide insights into sports information seeking behavior on the Internet. The developed method also may be applied to other query log subject areas.

Date: 2009
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jamist:v:60:y:2009:i:8:p:1550-1571

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https://doi.org/10.1002/(ISSN)1532-2890

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