Time gap analysis by the topic model-based temporal technique

• Published in: Journal of informetrics 2014-07, Vol.8 (3), p.776-790
• Main Authors: Jeong, Do-Heon, Song, Min
• Format: Article
• Language: English
• Subjects: Content analysis; Latent Dirichlet Allocation (LDA); Multiple resources; Temporal analysis; Text mining; Topic modeling
• ISSN: 1751-1577; 1875-5879
• DOI: 10.1016/j.joi.2014.07.005

•We provide in-depth understanding of various resources by analyzing contents and trends.•We measure exact time differences between academic disciplines by the time gap analysis.•We evaluate the topic modeling results by a statistical approach and content analysis of representative topics. This study proposes a temporal analysis method to utilize heterogeneous resources such as papers, patents, and web news articles in an integrated manner. We analyzed the time gap phenomena between three resources and two academic areas by conducting text mining-based content analysis. To this end, a topic modeling technique, Latent Dirichlet Allocation (LDA) was used to estimate the optimal time gaps among three resources (papers, patents, and web news articles) in two research domains. The contributions of this study are summarized as follows: firstly, we propose a new temporal analysis method to understand the content characteristics and trends of heterogeneous multiple resources in an integrated manner. We applied it to measure the exact time intervals between academic areas by understanding the time gap phenomena. The results of temporal analysis showed that the resources of the medical field had more up-to-date property than those of the computer field, and thus prompter disclosure to the public. Secondly, we adopted a power-law exponent measurement and content analysis to evaluate the proposed method. With the proposed method, we demonstrate how to analyze heterogeneous resources more precisely and comprehensively.