A lead‐lag analysis of the topic evolution patterns for preprints and publications. (2nd April 2015)

• Record Type: Journal Article
• Authors: Hu, Beibei; Dong, Xianlei; Zhang, Chenwei; Bowman, Timothy D.; Ding, Ying; Milojević, Staša; Ni, Chaoqun; Yan, Erjia; Larivière, Vincent
• Is Part Of: Journal of the Association for Information Science and Technology. Volume 66:Number 12(2015:Dec.)
• Page Start: 2643
• Page End: 2656
• Publication Date: 2015-04-02
• Subjects: preprints -- publications; Information science -- Periodicals; Information technology -- Periodicals; 020.5
• DOI: 10.1002/asi.23347
• Languages: English
• ISSNs: 2330-1635

Abstract

Abstract : This study applied LDA (latent Dirichlet allocation) and regression analysis to conduct a lead‐lag analysis to identify different topic evolution patterns between preprints and papers from arXiv and the Web of Science (WoS) in astrophysics over the last 20 years (1992–2011). Fifty topics in arXiv and WoS were generated using an LDA algorithm and then regression models were used to explain 4 types of topic growth patterns. Based on the slopes of the fitted equation curves, the paper redefines the topic trends and popularity. Results show that arXiv and WoS share similar topics in a given domain, but differ in evolution trends. Topics in WoS lose their popularity much earlier and their durations of popularity are shorter than those in arXiv. This work demonstrates that open access preprints have stronger growth tendency as compared to traditional printed publications.