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International Conference on Intelligent and Interactive Systems and Applications

IISA 2019: Advances in Intelligent Systems and Interactive Applications pp 303–311Cite as

Characteristics and Evolution of Citation Distance Based on LDA Method

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1084))

Abstract

The scientific research behavior of scholars is the core issue of scientific research. The research ideas and methods of complex networks provide a new perspective for the study of science. The scientific citation network and the scientist cooperation network are widely used to study the citation behavior of scholars and the dissemination of scientific ideas, and so far, some results have been obtained. However, due to the lack of information on the content of the article, the research based solely on the network topology has limitations and deficiencies. Combining the textual content analysis through LDA, this paper studies the distribution characteristics of content correlation between articles with citation relations and its evolution with time. It found that the distribution of citation distance has normal characteristics, but the reference distance is visible to be short. Authors have citation preferences for documents at a distance.

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References

  1. Jia, T., Wang, D., Szymanski, B.K.: Quantifying patterns of research-interest evolution. Nature Human Behaviour 1(4), 0078 (2017)

    Article  Google Scholar 

  2. Leydesdorff, L.: The Challenge of Scientometrics: the Development, Measurement, and Self-Organization of Scientific Communications. Universal-Publishers (2001)

    Google Scholar 

  3. Zeng, A., Shen, Z., Zhou, J., Wu, J., Fan, Y., Wang, Y., Stanley, H.E.: The science of science: from the perspective of complex systems. Phys. Rep. 714, 1–73 (2017)

    Article  MathSciNet  Google Scholar 

  4. Newman, M.E.J.: The structure of scientific collaboration networks. Proc. Natl. Acad. Sci. 98(2), 404–409 (2001)

    Article  MathSciNet  Google Scholar 

  5. Shibata, N., Kajikawa, Y., Takeda, Y., Matsushima, K.: Detecting emerging research fronts based on topological measures in citation networks of scientific publications. Technovation 28(11), 758–775 (2008)

    Article  Google Scholar 

  6. Radicchi, F., Fortunato, S., Markines, B., Vespignani, A.: Diffusion of scientific credits and the ranking of scientists. Phys. Rev. E 80(5), 056103 (2009)

    Article  Google Scholar 

  7. Li, Y., Li, H., Liu, N., Liu, X.: Important institutions of interinstitutional scientific collaboration networks in materials science. Scientometrics 117(1), 85–103 (2018)

    Article  Google Scholar 

  8. Zhou, Y.B., Lü, L., Li, M.: Quantifying the influence of scientists and their publications: distinguishing between prestige and popularity. New J. Phys. 14(3), 033033 (2012)

    Article  Google Scholar 

  9. An, W., Ding, Y.: The landscape of causal inference: perspective from citation network analysis. Am. Stat. 72(3), 265–277 (2018)

    Article  MathSciNet  Google Scholar 

  10. Gualdi, S., Medo, M., Zhang, Y.C.: Influence, originality and similarity in directed acyclic graphs. Europhys. Lett. 96(1), 18004 (2011)

    Article  Google Scholar 

  11. Shen, H.W., Barabási, A.L.: Collective credit allocation in science. Proc. Natl. Acad. Sci. 111(34), 12325–12330 (2014)

    Article  Google Scholar 

  12. Niu, Q., Zhou, J., Zeng, A., Fan, Y., Di, Z.R.: Which publication is your representative work? J. Inf. 10(3), 842–853 (2016)

    Google Scholar 

  13. Son, J., Kim, S.B.: Academic paper recommender system using multilevel simultaneous citation networks. Decis. Support Syst. 105, 24–33 (2018)

    Article  Google Scholar 

  14. Acuna, D.E., Allesina, S., Kording, K.P.: Future impact: predicting scientific success. Nature 489(7415), 201 (2012)

    Article  Google Scholar 

  15. Sebastiani, F.: Machine learning in automated text categorization. ACM Comput. Surv. (CSUR) 34(1), 1–47 (2002)

    Article  MathSciNet  Google Scholar 

  16. Saggion, H., Poibeau, T.: Automatic text summarization: past, present and future. In: Multi-source, Multilingual Information Extraction and Summarization, pp. 3–21. Springer Berlin Heidelberg (2013)

    Google Scholar 

  17. Kim, S.N., Medelyan, O., Kan, M.Y., Baldwin, T.: Automatic keyphrase extraction from scientific articles. Lang. Resour. Eval. 47(3), 723–742 (2013)

    Article  Google Scholar 

  18. Blei, D.M., Ng, A., Jordan, M.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2013)

    MATH  Google Scholar 

  19. Hantzsche, A., Kara, A., Young, G., Bates, J.M., Granger, C.W., Geweke, J., Amisano, G., Rossi, B., Elliott, G., Timmermann, A.: Latent Dirichlet allocation. Natl. Inst. Econ. Rev. 246(1), F4–F35 (2018)

    Article  Google Scholar 

Download references

Acknowledgments

We appreciate comments and helpful suggestions from Prof. Zengru Di, Prof. Chensheng Wu, Ms. Weiwei Gu. This work was supported by Chinese National Natural Science Foundation (71701018, 61673070 and 71671017).

Author information

Authors and Affiliations

  1. School of Systems Science, Beijing Normal University, Beijing, 100875, People’s Republic of China

    Benji Li, Xiaomeng Li, Qinghua Chen, Jianzhang Bao & Tao Zheng

  2. Department of Mathematics, University of California, Los Angeles, 90095, USA

    Yan Wang

Authors
  1. Benji Li
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  2. Yan Wang
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  3. Xiaomeng Li
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  4. Qinghua Chen
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  5. Jianzhang Bao
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  6. Tao Zheng
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Corresponding author

Correspondence to Qinghua Chen .

Editor information

Editors and Affiliations

  1. Dept De Ciències De La Computació, Universitat Politècnica De Catalunya, Barcelona, Spain

    Fatos Xhafa

  2. Department of Computer Science and Engineering, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  3. Department of Business Systems and Analytics, La Salle University, Philadelphia, PA, USA

    Madjid Tavana

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Li, B., Wang, Y., Li, X., Chen, Q., Bao, J., Zheng, T. (2020). Characteristics and Evolution of Citation Distance Based on LDA Method. In: Xhafa, F., Patnaik, S., Tavana, M. (eds) Advances in Intelligent Systems and Interactive Applications. IISA 2019. Advances in Intelligent Systems and Computing, vol 1084. Springer, Cham. https://doi.org/10.1007/978-3-030-34387-3_37

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