A cluster and content analysis of data mining studies in library and information science

Abstract

This study examines the use of data mining strategies in library and information science research journals, including the types of studies that use the strategy as well as most popular journals for publishing article that employ the strategies. A content and cluster analysis was performed with articles published in major LIS journals during the years 2006, 2012, and 2018. The Journal of the Association for Information Science and Technology had the most such articles with 42, with Information Processing and Management following close behind with 32. A cluster analysis performed based on word frequency in these articles’ abstracts identified three unique clusters associated with the topics of Publications/Citations, Consumer Behavior, and Information/Media Use. This analysis indicates a shift away from Publications/Citations towards more Consumer Behavior-based data mining studies. The findings of this study may be significant for current researchers in preparing and publishing their own data mining-based studies and determining avenues for publishing their work.