Abstract
Revealing the character of journals based on citation data remains an interesting issue nowadays. It aims to establish a reasonable journal evaluation system and provides suitable journals for scholars to submit to. As for traditional methods, based on first-order citation networks, they are poor at describing the multivariate sequential interactions among journals and at revealing their character. In this article, an efficient approach, namely, the recombination higher-order network algorithm, is proposed to well reveal the importance and complexity of journals in citation networks. Through the recombination of citation flow, the multivariate sequential data will be collected, which is a key step to structure a higher-order citation network. Combining with network topology features, the importance evaluation metrics are proposed from local and global perspectives respectively. The experiments in the empirical network demonstrate that compared with traditional methods, our method works better in identifying important journals. Besides, the higher-order complexity metric and the higher-order simplicity metric are designated as the complexity or simplicity evaluation metric in higher-order networks respectively, which better identify journal categories.
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Acknowledgements
Thanks Yangyang Liu and Xiaojie Wang a lot for valuable discussions. We thank the support from Higher-Order Network Reading Group supported by the Save 2050 Programme jointly sponsored by Swarma Club and X-Order. This document is the results of the research project funded by National Natural Science Foundation of China (Nos. 1171450, 62103422 and 62103375); National Key R & D Program of China (No. 2017YFC1200301); Natural Science Foundation of Hunan Province (No.2021JJ40675); Zhejiang Province Philosophy and Social Science Planning Key Project (No. 22NDJC009Z); and Postgraduate Scientific Research Innovation Project of Hunan Province (Nos. CX20200001 and QL20210003).
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LX-conceptualisation, data curation, formal analysis, investigation, methodology, visualisation, writing-original draft, and writing-review and editing. ZC-conceptualisation, formal analysis, supervision. HZ-writing-original draft, and writing-review and editing. YC-writing-original draft, and writing-review and editing. DX-conceptualisation, formal analysis, supervision, writing-original draft, and writing-review and editing.
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Appendices
Appendix
A name of journals
There are all 22 journals in APS used in this article, the importance and complexity are analyzed in higher-order networks respectively. In order to use the journals more easily, the codes and abbreviations of them are listed in Table 7, where the codes are used in Fig. 3, and the abbreviations are used in Figs. 3, 4, 5, 6, 7 and Tables 1, 2, 3, 4, 5, 6.
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Li, X., Zhao, C., Hu, Z. et al. Revealing the character of journals in higher-order citation networks. Scientometrics 127, 6315–6338 (2022). https://doi.org/10.1007/s11192-022-04518-z
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DOI: https://doi.org/10.1007/s11192-022-04518-z