Abstract
Intention usually refers to the intention to achieve a certain purpose, which is the realistic power to motivate people to act. At present, with the development of the Internet and social media, the scope of human activities is becoming larger and deeper. In the academic circle, the cooperation between scientific research workers is becoming closer and closer, and the activities of human beings and even the cooperative behaviors of scientific research workers contain the intentions of individuals or organizations. By extracting scientific citation data on the network, this paper constructs a spatial-temporal related scientific collaboration network, proposes a spatial-temporal distribution method of resources, and analyses and evaluates the behavioral intention of collaboration network. It mainly includes the visualization method of spatial-temporal distribution of resources of paper information, the spatial-temporal network modeling of paper cooperative intention, the analysis of intention evaluation model and so on. Finally, the problems and possible challenges in the future research are prospected.
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References
Barabási, A.-L.: The new science of networks. Phys. Today 6(5), 243–270 (2003). https://doi.org/10.2307/20033300
Watts, D.J.: The “new” science of networks. Ann. Rev. Sociol. 30(1), 243–270 (2004). https://doi.org/10.1146/annurev.soc.30.020404.104342
Dereian, P., Hummon, P.: North-Holland connectivity in a citation network: the development of dna theory*. Soc. Netw. 11(1), 39–63 (1989). https://doi.org/10.1016/0378-8733(89)90017-8
Newman, M.E.J.: The structure and function of complex networks. SIAM Rev. 45(2), 167–256 (2003). https://doi.org/10.1137/S003614450342480
Kretschmer, H., Kretschmer, T.: A new centrality measure for social network analysis applicable to bibliometric and webometric data. In: International Conference on Digital Information Management IEEE (2006). https://doi.org/10.1109/ICDIM.2007.369353
Xiaoming, L., et al.: Co-authorship networks in the digital library research community. Inf. Process. Manag. 41(6), 1462–1480 (2005). https://doi.org/10.1016/j.ipm.2005.03.012
Börner, K., et al.: Studying the emerging global brain: analyzing and visualizing the impact of co-authorship teams. Complexity 10(4), 57–67 (2005). https://doi.org/10.1002/cplx.20078
Ichise, R., Takeda, H., Muraki, T.: A discovery method of research communities. In: Proceedings of Adaptation in Artificial Biological Systems, no. 3, pp. 1 28–1 31 (2006)
Ichise, R., Takeda, H., Muraki, T.: Research community mining with topic identification. In: International Conference on Information Visualization (2006)
Basu, P., et al.: Modeling and analysis of time-varying graphs. arXiv preprint arXiv:1012.0260 (2010)
Kolar, M., et al.: Estimating time-varying networks. Ann. Appl. Stat. 4(1), 94–123 (2010). https://doi.org/10.1214/09-AOAS308
Martin, R., Bergstrom, C.T., Fabio, R.: Mapping change in large networks. PLoS One 5(1), e8694 (2010). https://doi.org/10.1371/journal.pone.0008694
Casteigts, A., et al.: Time-varying graphs and dynamic networks. Int. J. Parallel Emergent Distrib. Syst. 27(5), 387–408 (2010)
Holme, P., Saramäki, J.: Temporal networks as a modeling framework. Understanding Complex Systems, pp. 1–14 (2013)
Bassett, D.S., et al.: Cross-linked structure of network evolution. Chaos 24(1), 97–386 (2014). https://doi.org/10.1063/1.4858457
Acknowledgments
This work is partially supported by the National Key R&D Program of China (Grant No. 2017YCF1200301).
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Zhang, N., Zhao, C., Zhang, X., Yi, D. (2020). A Method of Intention Discovery Based on Scientific Collaboration Information. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_114
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DOI: https://doi.org/10.1007/978-3-030-32591-6_114
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