Does Granger causality exist between article usage and publication counts? A topic-level time-series evidence from IEEE Xplore

Wencan Tian, Yongzhen Wang, Zhigang Hu, Ruonan Cai, Guangyao Zhang and Xianwen Wang ()
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Wencan Tian: Dalian University of Technology
Yongzhen Wang: Dalian University of Technology
Zhigang Hu: South China Normal University
Ruonan Cai: Shandong University
Guangyao Zhang: Dalian University of Technology
Xianwen Wang: Dalian University of Technology

Scientometrics, 2024, vol. 129, issue 6, No 15, 3285-3302

Abstract: Abstract In this study, employing the IEEE Xplore database as the data source, articles on different topics (keywords) and their usage data generated from January 2011 to December 2020 were collected and analyzed. The study examined the temporal relationships between these usage data and publication counts at the topic level via Granger causality analysis. The study found that almost 80% of the topics exhibit significant usage-publication interactions from a time-series perspective, with varying time lag lengths depending on the direction of the Granger causality results. Topics that present bidirectional Granger causality show longer time lag lengths than those exhibiting unidirectional causality. Additionally, the study found that the direction of the unidirectional Granger causality was influenced by the significance of a topic. Topics with a greater preference for article usage as the Granger cause of publication counts were deemed more important. The findings’ reliability was confirmed by varying the maximum lag period. This study provides strong support for using usage data to identify hot topics of research.

Keywords: Article usage data; Publication counts; IEEE Xplore; Time-series; Granger causality test (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11192-024-05038-8

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