Abstract
Does main path analysis (MPA), in producing the main paths (MPs), invariably choose the longer paths over the shorter ones? This work examines the various combinations of the most popular path search algorithms, i.e., local and global searches (including the key-route variant), and the weight assignment algorithms, i.e., search path count (SPC), search path link count (SPLC), and search path node pair (SPNP), to investigate the path preference of MPA. Based on a simplified model, this work finds that, when there are multiple paths between a pair of nodes, MPA indeed goes for the longer paths under some, but not all, algorithm combinations, but it may retain both longer and shorter paths under other combinations.
References
Batagelj, V. (2003). Efficient algorithms for citation network analysis. Preprint at http://arXiv.org/cs/0309023
Batagelj, V., & Mrvar, A. (1998). Pajek—Program for large network analysis. Connections, 21(2), 47–57.
Chen, L., Xu, S., Zhu, L., Zhang, J., Xu, H., & Yang, G. (2022). A semantic main path analysis method to identify multiple developmental trajectories. Journal of Informetrics, 16(2), 101281.
Choi, C., & Park, Y. (2009). Monitoring the organic structure of technology based on the patent development paths. Technological Forecasting and Social Change, 76(6), 754–768.
De Nooy, W., Mrvar, A., & Batagelj, V. (2018). Exploratory social network analysis with Pajek: Revised and expanded edition for updated software (Vol. 46). Cambridge University Press.
Hummon, N. P., & Doreian, P. (1989). Connectivity in a citation network: The development of DNA theory. Social Networks, 11(1), 39–63.
Jiang, X., Zhu, X., & Chen, J. (2020). Main path analysis on cyclic citation networks. Journal of the Association for Information Science and Technology, 71(5), 578–595.
Kim, E. H., Jeong, Y. K., Kim, Y., & Song, M. (2022). Exploring scientific trajectories of a large-scale dataset using topic-integrated path extraction. Journal of Informetrics, 16(1), 101242.
Kuan, C. H., Chen, D. Z., & Huang, M. H. (2019). Bibliographically coupled patents: Their temporal pattern and combined relevance. Journal of Informetrics, 13(4), 100978.
Liu, J. S., & Lu, L. Y. (2012). An integrated approach for main path analysis: Development of the Hirsch index as an example. Journal of the American Society for Information Science and Technology, 63(3), 528–542.
Lu, Z., Ma, Y., & Song, L. (2021). Patent citation network analysis based on improved main path analysis: Mapping key technology trajectory. In International conference on artificial intelligence and security (pp. 158–171). Springer.
Park, H., & Magee, C. L. (2017). Tracing technological development trajectories: A genetic knowledge persistence-based main path approach. PLoS ONE, 12(1), e0170895.
Šubelj, L., Waltman, L., Traag, V., & van Eck, N. J. (2020). Intermediacy of publications. Royal Society Open Science, 7(1), 190207.
Xu, S., Wang, C., An, X., Hao, L., & Yang, G. (2022). A novel developmental trajectory discovery approach by integrating main path analysis and intermediacy. Journal of Information Science. https://doi.org/10.1177/01655515221101835
Yoon, S., Mun, C., Raghavan, N., Hwang, D., Kim, S., & Park, H. (2020). Hierarchical main path analysis to identify decompositional multi-knowledge trajectories. Journal of Knowledge Management, 25(2), 454–476.
Yu, D., & Pan, T. (2021). Tracing the main path of interdisciplinary research considering citation preference: A case from blockchain domain. Journal of Informetrics, 15(2), 101136.
Acknowledgements
The author expresses his appreciation to the anonymous reviewers for their careful examination of the manuscript and their helpful comments and suggestions. This work was financially supported by the Center for Research in Econometric Theory and Applications (Grant No. 111L900204) from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project, the Universities and Colleges Humanities and Social Sciences Benchmarking Project (Grant No. 111L9A002) by the Ministry of Education (MOE) in Taiwan, and by the Ministry of Science and Technology (MOST), Taiwan, under Grant Nos. 111-2634-F-002-018- and 110-2221-E-011-141-.
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Kuan, CH. Does main path analysis prefer longer paths?. Scientometrics 128, 841–851 (2023). https://doi.org/10.1007/s11192-022-04543-y
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DOI: https://doi.org/10.1007/s11192-022-04543-y