In today's digital age, daily reading may be becoming digital reading. To understand this possible shift from reading print media to reading digital media, we investigated reading behavior for 11 media and reading preferences between print and digital in different circumstances. In August 2012, an online survey was used to inquire about the reading behavior and preference of 1,755 participants, ranging in age from 18 to 69 years. The participants contained equal numbers of men and women from five age brackets. Our main finding was that approximately 70% of total reading time was spent on digital media and that preferences favored print media. Cluster analysis of reading time by media was used to categorize respondents into eight clusters, and a second cluster analysis on stated preference (digital or print) yielded six clusters. The correspondence analysis between reading behavior clusters and preference clusters revealed that there is a mismatch between reading behavior and stated preference for either print or digital media.

The purpose of this research is to identify topics in library and information science (LIS) using latent Dirichlet allocation (LDA) and to visualize the knowledge structure of the field as consisting of specific topics and its transition from 2000–2002 to 2015–2017. The full text of 1648 research articles from five peer-reviewed representative LIS journals in these two periods was analyzed by using LDA. A total of 30 topics in each period were labeled based on the frequency of terms and the contents of the articles. These topics were plotted on a two-dimensional map using LDAvis and categorized based on their location and characteristics in the plots. Although research areas in some forms were persistent with which discovered in previous studies, they were crucial to the transition of the knowledge structure in LIS and had the following three features: (1) The Internet became the premise of research in LIS in 2015–2017. (2) Theoretical approach or empirical work can be considered as a factor in the transition of the knowledge structure in some categories. (3) The topic diversity of the five core LIS journals decreased from the 2000–2002 to 2015–2017.

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The topic modeling approach can indicate hidden relationships between articles in a particular academic discipline. This study aims to examine topics in library and information science (LIS) using the latent Dirichlet allocation method. From representative five journals, 1,648 full‐text articles were analyzed. We labeled 30 identified topics based on the top 10 highly weighted terms for each topic, title, and body of articles. From the topic mapping, commonly used methods and shift of research issues in LIS were found.

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