[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Springer Nature Link
Log in

CLARA: citation and similarity-based author ranking

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

Scientific collaboration is getting tremendous attention from scholars and becoming the most common way of producing research works from different disciplines, enabling them to solve complex problems. Nevertheless, when the number of collaborators increases in research work, it becomes challenging to single out and recognize one scholar who contributes the most to the collaboration team of multiauthored publications. Hence, determining an influential author either from multiauthored papers or co-authorship networks is an interesting research problem. To address these problems, we develop a citation and similarity-based author ranking method, namely CLARA, that captures the influential author in multiauthored publications. The method considers attributes of publications such as citing papers and co-cited papers and similarity between publications. Firstly, the method computes the contribution of the co-authors in a given paper by employing fractional counting metrics. Secondly, it computes the contextual similarity between the given paper and its co-cited papers. Finally, the method ranks each co-author using the mathematically defined metric, called KeyScore, and discovers the “key” author among the co-authors of the given paper. We validate our method by extracting the papers of the “Chinese Outstanding Youth” winning researchers from the Microsoft Academic Graph dataset. The experimental results show that the CLARA method performs well in identifying key authors accurately and effectively, despite the position of the authors in the author list of their corresponding papers.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. https://scholar.google.com/citations?user=rQ68pVwAAAAJ &hl=en &oi=sra.

  2. http://research.microsoft.com/en-us/projects/mag/.

  3. https://radimrehurek.com/gensim/.

  4. http://research.microsoft.com/en-us/projects/mag/.

  5. https://disamby.readthedocs.io.

References

  • Alshareef, A. M., Alhamid, M. F., & El Saddik, A. (2019). Academic venue recommendations based on similarity learning of an extended nearby citation network. IEEE Access, 7, 38813–38825. https://doi.org/10.1109/ACCESS.2019.2906106

    Article  Google Scholar 

  • Amjad, T., Bibi, S., Shaikh, M., & Daud, A. (2016). Author productivity indexing via topic sensitive weighted citations. Science International, 28(4), 4135–4139.

    Google Scholar 

  • Amjad, T., & Daud, A. (2017). Indexing of authors according to their domain of expertise. Malaysian Journal of Library & Information Science, 22(1), 69–82. https://doi.org/10.22452/mjlis.vol22no1.6

    Article  Google Scholar 

  • Amjad, T., Daud, A., & Aljohani, N. R. (2018). Ranking authors in academic social networks: A survey. Library Hi Tech, 36(1), 97–128. https://doi.org/10.1108/LHT-05-2017-0090

    Article  Google Scholar 

  • Bai, X., Pan, H., Hou, J., Guo, T., Lee, I., & Xia, F. (2020). Quantifying success in science: An overview. IEEE Access, 8, 123200–123214.

    Article  Google Scholar 

  • Bao, P., & Zhai, C. (2017). Dynamic credit allocation in scientific literature. Scientometrics, 112(1), 595–606. https://doi.org/10.1007/s11192-017-2335-9

    Article  Google Scholar 

  • Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022.

    MATH  Google Scholar 

  • Cai, L., Tian, J., Liu, J., Bai, X., Lee, I., Kong, X., & Xia, F. (2019). Scholarly impact assessment: A survey of citation weighting solutions. Scientometrics, 118(2), 453–478.

    Article  Google Scholar 

  • Chang, L. L. H., Phoa, F. K. H., & Nakano, J. (2019). A new metric for the analysis of the scientific article citation network. IEEE Access, 7, 132027–132032. https://doi.org/10.1109/ACCESS.2019.2937220

    Article  Google Scholar 

  • Coccia, M., & Wang, L. (2016). Evolution and convergence of the patterns of international scientific collaboration. Proceedings of the National Academy of Sciences, 113(8), 2057–2061. https://doi.org/10.1073/pnas.1510820113

    Article  Google Scholar 

  • DeHart, D. (2017). Team science: A qualitative study of benefits, challenges, and lessons learned. The Social Science Journal, 54(4), 458–467. https://doi.org/10.1016/j.soscij.2017.07.009

    Article  Google Scholar 

  • Ding, J., Liu, C., Zheng, Q., & Cai, W. (2021). A new method of co-author credit allocation based on contributor roles taxonomy: Proof of concept and evaluation using papers published in plos one. Scientometrics, 126(9), 7561–7581.

    Article  Google Scholar 

  • Dong, Y., Ma, H., Shen, Z., & Wang, K. (2017). A century of science: Globalization of scientific collaborations, citations, and innovations. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, ACM, New York, NY, USA (pp. 1437–1446). https://doi.org/10.1145/3097983.3098016

  • Egghe, L. (2006). Theory and practise of the g-index. Scientometrics, 69(1), 131–152. https://doi.org/10.1007/s11192-006-0144-7

    Article  Google Scholar 

  • Farooq, M., Khan, H. U., Iqbal, S., Munir, E. U., & Shahzad, A. (2017). Ds-index: Ranking authors distinctively in an academic network. IEEE Access, 5, 19588–19596. https://doi.org/10.1109/ACCESS.2017.2744798

    Article  Google Scholar 

  • Fortunato, S., Bergstrom, C. T., Börner, K., Evans, J. A., Helbing, D., Milojević, S., Petersen, A. M., Radicchi, F., Sinatra, R., Uzzi, B., Vespignani, A., Waltman, L., Wang, D., & Barabási, A. L. (2018). Science of science. Science. https://doi.org/10.1126/science.aao0185.

    Article  Google Scholar 

  • Guan, J., Zuo, K., Chen, K., & Yam, R. C. (2016). Does country-level R & D efficiency benefit from the collaboration network structure? Research Policy, 45(4), 770–784. https://doi.org/10.1016/j.respol.2016.01.003

    Article  Google Scholar 

  • Hagen, N. T. (2008). Harmonic allocation of authorship credit: Source-level correction of bibliometric bias assures accurate publication and citation analysis. PLoS ONE, 3(12), 4021. https://doi.org/10.1371/journal.pone.0004021

    Article  Google Scholar 

  • Han, J., Pei, J., & Kamber, M. (2011). Data mining: Concepts and techniques. Berlin: Elsevier Science.

    MATH  Google Scholar 

  • Hirsch, J. E. (2005). An index to quantify an individual’s scientific research output. Proceedings of the National Academy of Sciences of the United States of America, 102(46), 16569. https://doi.org/10.1073/pnas.0507655102

    Article  MATH  Google Scholar 

  • Jung, S., & Yoon, W. C. (2019). Citation-based author contribution measure for byline-independency. In 2019 IEEE International Conference on Big Data (Big Data), IEEE, Los Angeles, CA, United States (pp 6086–6088). https://doi.org/10.1109/BigData47090.2019.9006230

  • Kataria, S., Mitra, P., Caragea, C., & Giles, C. L. (2011). Context sensitive topic models for author influence in document networks. In Twenty-Second International Joint Conference on Artificial Intelligence, IJCAI, Barcelona, Spain.

  • Kim, J., & Diesner, J. (2014). A network-based approach to coauthorship credit allocation. Scientometrics, 101(1), 587–602. https://doi.org/10.1007/s11192-014-1253-3

    Article  Google Scholar 

  • Knoke, D., & Yang, S. (2019). Social network analysis (Vol. 154). Berlin: SAGE Publications.

    Google Scholar 

  • Kong, X., Jiang, H., Yang, Z., Xu, Z., & Xia, F., & Tolba, A. (2016). Exploiting publication contents and collaboration networks for collaborator recommendation. PLoS ONE, 11(2), 0148492. https://doi.org/10.1371/journal.pone.0148492

    Article  Google Scholar 

  • Kong, X., Mao, M., Jiang, H., Yu, S., & Wan, L. (2019). How does collaboration affect researchers’ positions in co-authorship networks? Journal of Informetrics, 13(3), 887–900. https://doi.org/10.1016/j.joi.2019.07.005

    Article  Google Scholar 

  • Kong, X., Zhang, J., Zhang, D., Bu, Y., Ding, Y., & Xia, F. (2020). The gene of scientific success. ACM Transactions on Knowledge Discovery from Data, 14(4), 1–19.

    Article  Google Scholar 

  • Le, Q., & Mikolov, T. (2014). Distributed representations of sentences and documents. In International Conference on Machine Learning (pp. 1188–1196). JMLR.

  • Li, T., Mei, T., Kweon, I. S., & Hua, X. S. (2010). Contextual bag-of-words for visual categorization. IEEE Transactions on Circuits and Systems for Video Technology, 21(4), 381–392. https://doi.org/10.1109/TCSVT.2010.2041828

    Article  Google Scholar 

  • Li, X., Verginer, L., Riccaboni, M., & Panzarasa, P. (2022). A network approach to expertise retrieval based on path similarity and credit allocation. Journal of Economic Interaction and Coordination, 17(2), 501–533.

    Article  Google Scholar 

  • Liu, J., Kong, X., Zhou, X., Wang, L., Zhang, D., Lee, I., Xu, B., & Xia, F. (2019). Data mining and information retrieval in the 21st century: A bibliographic review. Computer, 34, 100193.

    MathSciNet  Google Scholar 

  • Liu, J., Tian, J., Kong, X., Lee, I., & Xia, F. (2019). Two decades of information systems: A bibliometric review. Scientometrics, 118(2), 617–643.

    Article  Google Scholar 

  • Mikolov, T., Sutskever, I., Chen, K., Corrado, G. S., & Dean, J. (2013). Distributed representations of words and phrases and their compositionality. Advances in neural information processing systems, neural information processing systems (pp. 3111–3119).

  • Perianes-Rodriguez, A., Waltman, L., & Van Eck, N. J. (2016). Constructing bibliometric networks: A comparison between full and fractional counting. Journal of Informetrics, 10(4), 1178–1195. https://doi.org/10.1016/j.joi.2016.10.006

    Article  Google Scholar 

  • Ren, J., Wang, L., Wang, K., Yu, S., Hou, M., Lee, I., Kong, X., & Xia, F. (2019). Api: An index for quantifying a scholar’s academic potential. IEEE Access, 7, 178675–178684. https://doi.org/10.1109/ACCESS.2019.2958649

    Article  Google Scholar 

  • Saberi, M. K., Mokhtari, H., Mirezati, S. Z., Ansari, N., & Mohammadian, S. (2022). Co-authorship networks of Iranian researchers’ publications on the field of management during a half-century (1969–2018). International Journal of Information Science and Management (IJISM), 20(1), 1.

    Google Scholar 

  • Sachmpazidi, D., Olmstead, A., Thompson, A. N., Henderson, C., & Beach, A. (2021). Team-based instructional change in undergraduate stem: Characterizing effective faculty collaboration. International Journal of STEM Education, 8(1), 1–23.

    Article  Google Scholar 

  • Sarli, C. C., & Carpenter, C. R. (2014). Measuring academic productivity and changing definitions of scientific impact. Missouri Medicine, 111(5), 399.

    Google Scholar 

  • Schubert, A. (2011). A hirsch-type index of co-author partnership ability. Scientometrics, 91(1), 303–308. https://doi.org/10.1007/s11192-011-0559-7

    Article  Google Scholar 

  • Shen, H.W., & Barabási, A.L. (2014). Collective credit allocation in science. Proceedings of the National Academy of Sciences, 111(34), 12325–12330.

    Article  Google Scholar 

  • Tol, R. S. (2011). Credit where credit’s due: Accounting for co-authorship in citation counts. Scientometrics, 89(1), 291. https://doi.org/10.1007/s11192-011-0451-5

    Article  Google Scholar 

  • Trueba, F. J., & Guerrero, H. (2004). A robust formula to credit authors for their publications. Scientometrics, 60(2), 181–204. https://doi.org/10.1023/b:scie.0000027792.09362.3f

    Article  Google Scholar 

  • Tu, Y., Johri, N., Roth, D., & Hockenmaier, J. (2010). Citation author topic model in expert search. In Proceedings of the 23rd International Conference on Computational Linguistics: Posters, Association for Computational Linguistics, Stroudsburg, PA, USA (pp. 1265–1273).

  • Turner, J. R., & Baker, R. (2020). Collaborative research: Techniques for conducting collaborative research from the science of team science (scits). Advances in Developing Human Resources. https://doi.org/10.1177/1523422319886300

    Article  Google Scholar 

  • Usmani, A., & Daud, A. (2017). Unified author ranking based on integrated publication and venue rank. International Arab Journal of Information Technology, 14(1), 5. https://doi.org/10.1016/j.joi.2018.11.005

    Article  Google Scholar 

  • Walker, D., Xie, H., Yan, K. K., & Maslov, S. (2007). Ranking scientific publications using a model of network traffic. Journal of Statistical Mechanics: Theory and Experiment, 2007(06), P06010. https://doi.org/10.1088/1742-5468/2007/06/P06010

    Article  Google Scholar 

  • Waltman, L. (2012). An empirical analysis of the use of alphabetical authorship in scientific publishing. Journal of Informetrics, 6(4), 700–711. https://doi.org/10.1016/j.joi.2012.07.008

    Article  MathSciNet  Google Scholar 

  • Waltman, L. (2016). A review of the literature on citation impact indicators. Journal of Informetrics, 10(2), 365–391. https://doi.org/10.1016/j.joi.2016.02.007

    Article  Google Scholar 

  • Wang, J. P., Guo, Q., Zhou, L., & Liu, J. G. (2019). Dynamic credit allocation for researchers. Physica A: Statistical Mechanics and its Applications, 520, 208–216. https://doi.org/10.1016/j.physa.2019.01.011

    Article  Google Scholar 

  • Wang, K., Shen, Z., Huang, C. Y., Wu, C. H., Eide, D., Dong, Y., Qian, J., Kanakia, A., Chen, A., & Rogahn, R. (2019). A review of microsoft academic services for science of science studies. Frontiers in Big Data, 2, 45. https://doi.org/10.3389/fdata.2019.00045

    Article  Google Scholar 

  • Wang, M., Ren, J., Li, S., & Chen, G. (2019). Quantifying a paper’s academic impact by distinguishing the unequal intensities and contributions of citations. IEEE Access, 7, 96198–96214. https://doi.org/10.1109/ACCESS.2019.2927016

    Article  Google Scholar 

  • Wu, L., Kittur, A., Youn, H., Milojević, S., Leahey, E., Fiore, S. M., & Ahn, Y. Y. (2022). Metrics and mechanisms: Measuring the unmeasurable in the science of science. Journal of Informetrics, 16(2), 101290.

    Article  Google Scholar 

  • Wu, L., Wang, D., & Evans, J. A. (2019). Large teams develop and small teams disrupt science and technology. Nature, 566(7744), 378–382. https://doi.org/10.1038/s41586-019-0941-9

    Article  Google Scholar 

  • Xia, F., Liu, J., Nie, H., Fu, Y., Wan, L., & Kong, X. (2019). Random walks: A review of algorithms and applications. IEEE Transactions on Emerging Topics in Computational Intelligence, 4(2), 95–107.

    Article  Google Scholar 

  • Xia, F., Liu, J., Ren, J., Wang, W., & Kong, X. (2020). Turing number: How far are you to am turing award? In ACM SIGWEB Newsletter (Autumn) (pp. 1–8).

  • Xia, F., Wang, W., Bekele, T. M., & Liu, H. (2017). Big scholarly data: A survey. IEEE Transactions on Big Data, 3(1), 18–35. https://doi.org/10.1109/TBDATA.2016.2641460

    Article  Google Scholar 

  • Xing, Y., Wang, F., Zeng, A., & Ying, F. (2021). Solving the cold-start problem in scientific credit allocation. Journal of Informetrics, 15(3), 101157.

    Article  Google Scholar 

  • Xu, F., Wu, L., & Evans, J. (2022). Flat teams drive scientific innovation. Proceedings of the National Academy of Sciences, 119(23), e2200927119.

    Article  Google Scholar 

  • Yang, S., Xiao, A., Nie, Y., & Dong, J. (2022). Measuring coauthors’ credit in medicine field-based on author contribution statement and citation context analysis. Information Processing & Management, 59(3), 102924.

    Article  Google Scholar 

  • Yu, S., Bedru, H. D., Lee, I., & Xia, F. (2019). Science of scientific team science: A survey. Computer Science Review, 31, 72–83. https://doi.org/10.1016/j.cosrev.2018.12.001

    Article  Google Scholar 

  • Yu, S., Xia, F., Zhang, C., Wei, H., & Keogh, K., & Chen, H. (2021). Familiarity-based collaborative team recognition in academic social networks. IEEE Transactions on Computational Social Systems, 9, 5.

    Google Scholar 

  • Yu, S., Xia, F., Zhang, K., Ning, Z., Zhong, J., & Liu, C. (2017). Team recognition in big scholarly data: Exploring collaboration intensity. In 2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing, 3rd Intl Conf on Big Data Intelligence and Computing and Cyber Science and Technology Congress (DASC/PiCom/DataCom/CyberSciTech), IEEE, Orlando, FL, USA (pp. 925–932). https://doi.org/10.1109/DASC-PICom-DataCom-CyberSciTec.2017.155

  • Zarezadeh, S., & Ashrafi, S., & Asadi, M. (2018). Network reliability modeling based on a geometric counting process. Mathematics, 6(10), 0197. https://doi.org/10.3390/math6100197

    Article  Google Scholar 

  • Zhang, J., Ning, Z., Bai, X., Wang, W., Yu, S., & Xia, F. (2016). Who are the rising stars in academia? In 2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL), IEEE (pp. 211–212).

  • Zhang, J., Wang, W., Xia, F., Lin, Y. R., & Tong, H. (2020). Data-driven computational social science: A survey. Big Data Research, 21, 100145.

    Article  Google Scholar 

  • Zhang, Y., Wang, M., Gottwalt, F., Saberi, M., & Chang, E. (2019). Ranking scientific articles based on bibliometric networks with a weighting scheme. Journal of Informetrics, 13(2), 616–634. https://doi.org/10.1016/j.joi.2019.03.013

    Article  Google Scholar 

  • Zhao, F., Zhang, Y., Lu, J., & Shai, O. (2019). Measuring academic influence using heterogeneous author-citation networks. Scientometrics, 118(3), 1119–1140. https://doi.org/10.1007/s11192-019-03010-5

    Article  Google Scholar 

Download references

Acknowledgements

This work is partially supported by the Fundamental Research Funds for the Central Universities under Grant No. DUT22RC(3)060.

Author information

Authors and Affiliations

  1. School of Software, Dalian University of Technology, Dalian, 116620, China

    Chen Zhang

  2. School of Computer Science and Technology, University of Science and Technology of China, Hefei, 230000, China

    Iftikhar Hussain

  3. School of Computer, National University of Defense Technology, Changsha, Hunan, 410000, China

    Feng Xie

  4. School of Computer Science and Engineering, Central South University, Changsha, Hunan, 410083, China

    Hayat D. Bedru

  5. School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning, 116024, China

    Shuo Yu

Authors
  1. Hayat D. Bedru
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chen Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Feng Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Shuo Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Iftikhar Hussain
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shuo Yu.

Ethics declarations

Conflict of interest

The authors have no competing interests to declare that are relevant to the content of this article.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Bedru, H.D., Zhang, C., Xie, F. et al. CLARA: citation and similarity-based author ranking. Scientometrics 128, 1091–1117 (2023). https://doi.org/10.1007/s11192-022-04590-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-022-04590-5

Keywords

Search

Navigation