Logo image
Back
A lead‐lag analysis of the topic evolution patterns for preprints and publications
Journal article

A lead‐lag analysis of the topic evolution patterns for preprints and publications

Beibei Hu, Xianlei Dong, Chenwei Zhang, Timothy D Bowman, Ying Ding, Staša Milojević, Chaoqun Ni, Erjia Yan and Vincent Larivière
Journal of the Association for Information Science and Technology, v 66(12), pp 2643-2656
Dec 2015
DOI: https://doi.org/10.1002/asi.23347

Abstract

preprints publications
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.

Metrics

11 Record Views
18 citations in Web of Science
20 citations in Scopus

Details

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Computer Science, Information Systems
Information Science & Library Science
Logo image