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Scientific community detection via bipartite scholar/journal graph co-clustering

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  • Carusi, Chiara
  • Bianchi, Giuseppe
Abstract
This paper stems from the observation that researchers in different fields tend to publish in different journals. Such a relationship between researchers and journals is quantitatively exploited to identify scientific community clusters, by casting the community detection problem into a co-clustering problem on bipartite graphs. Such an approach has the potential of leading not only to the fine- grained detection of scholar communities based on the similarity of their research activity, but also to the clustering of scientific journals based on which are the most representative of each community. The proposed methodology is purely data-driven and completely unsupervised, and does not rely on any semantics (e.g. keywords or a-priori subjective categories). Moreover, unlike “flat” data structures (e.g. collaboration graphs or citation graphs) our bipartite graph approach blends in a joint structure both the researcher's attitude and interests (i.e., freedom to select the venue where to publish) as well as the community's recognition (i.e., acceptance of the publication on a target journal); as such may perhaps inspire further scientometric evaluation strategies. Our proposed approach is applied to the Italian research system, for two broad areas (ICT and Microbiology&Genetics), and reveals some questionable aspects and community overlaps in the current Italian scientific sectors classification.

Suggested Citation

  • Carusi, Chiara & Bianchi, Giuseppe, 2019. "Scientific community detection via bipartite scholar/journal graph co-clustering," Journal of Informetrics, Elsevier, vol. 13(1), pages 354-386.
    • Handle: RePEc:eee:infome:v:13:y:2019:i:1:p:354-386
    DOI: 10.1016/j.joi.2019.01.004
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    1. David Minguillo, 2010. "Toward a new way of mapping scientific fields: Authors' competence for publishing in scholarly journals," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(4), pages 772-786, April.
    2. Wang, Qi & Waltman, Ludo, 2016. "Large-scale analysis of the accuracy of the journal classification systems of Web of Science and Scopus," Journal of Informetrics, Elsevier, vol. 10(2), pages 347-364.
    3. Clara Calero & Renald Buter & Cecilia Cabello Valdés & Ed Noyons, 2006. "How to identify research groups using publication analysis: an example in the field of nanotechnology," Scientometrics, Springer;Akadémiai Kiadó, vol. 66(2), pages 365-376, February.
    4. Ludo Waltman & Nees Jan van Eck, 2012. "A new methodology for constructing a publication‐level classification system of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    5. Lovro Šubelj & Nees Jan van Eck & Ludo Waltman, 2016. "Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-23, April.
    6. Gergely Palla & Imre Derényi & Illés Farkas & Tamás Vicsek, 2005. "Uncovering the overlapping community structure of complex networks in nature and society," Nature, Nature, vol. 435(7043), pages 814-818, June.
    7. Kevin W. Boyack & Richard Klavans & Katy Börner, 2005. "Mapping the backbone of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 351-374, August.
    8. Perianes-Rodriguez, Antonio & Ruiz-Castillo, Javier, 2017. "A comparison of the Web of Science and publication-level classification systems of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 32-45.
    9. Leydesdorff, Loet & Rafols, Ismael, 2011. "Indicators of the interdisciplinarity of journals: Diversity, centrality, and citations," Journal of Informetrics, Elsevier, vol. 5(1), pages 87-100.
    10. Ludo Waltman & Nees Jan Eck, 2012. "A new methodology for constructing a publication-level classification system of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2378-2392, December.
    11. Richard Klavans & Kevin W. Boyack, 2017. "Which Type of Citation Analysis Generates the Most Accurate Taxonomy of Scientific and Technical Knowledge?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 984-998, April.
    12. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Di Costa, 2012. "Identifying interdisciplinarity through the disciplinary classification of coauthors of scientific publications," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(11), pages 2206-2222, November.
    13. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Costa, 2012. "Identifying interdisciplinarity through the disciplinary classification of coauthors of scientific publications," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(11), pages 2206-2222, November.
    14. Rodriguez, Marko A. & Pepe, Alberto, 2008. "On the relationship between the structural and socioacademic communities of a coauthorship network," Journal of Informetrics, Elsevier, vol. 2(3), pages 195-201.
    15. David Minguillo, 2010. "Toward a new way of mapping scientific fields: Authors' competence for publishing in scholarly journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(4), pages 772-786, April.
    16. Antonio Perianes-Rodríguez & Carlos Olmeda-Gómez & Félix Moya-Anegón, 2010. "Detecting, identifying and visualizing research groups in co-authorship networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 307-319, February.
    17. Richard Klavans & Kevin W. Boyack, 2009. "Toward a consensus map of science," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(3), pages 455-476, March.
    18. Wolfgang Glänzel & András Schubert, 2003. "A new classification scheme of science fields and subfields designed for scientometric evaluation purposes," Scientometrics, Springer;Akadémiai Kiadó, vol. 56(3), pages 357-367, March.
    19. Barabási, A.L & Jeong, H & Néda, Z & Ravasz, E & Schubert, A & Vicsek, T, 2002. "Evolution of the social network of scientific collaborations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 311(3), pages 590-614.
    20. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2011. "National-scale research performance assessment at the individual level," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 347-364, February.
    21. Nees Jan Eck & Ludo Waltman, 2017. "Citation-based clustering of publications using CitNetExplorer and VOSviewer," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(2), pages 1053-1070, May.
    22. Ruiz-Castillo, Javier & Waltman, Ludo, 2015. "Field-normalized citation impact indicators using algorithmically constructed classification systems of science," Journal of Informetrics, Elsevier, vol. 9(1), pages 102-117.
    23. Henk F. Moed & Gali Halevi, 2014. "A bibliometric approach to tracking international scientific migration," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(3), pages 1987-2001, December.
    24. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Murgia, Gianluca, 2013. "The collaboration behaviors of scientists in Italy: A field level analysis," Journal of Informetrics, Elsevier, vol. 7(2), pages 442-454.
    25. Félix Moya-Anegón & Benjamín Vargas-Quesada & Victor Herrero-Solana & Zaida Chinchilla-Rodríguez & Elena Corera-Álvarez & Francisco J. Munoz-Fernández, 2004. "A new technique for building maps of large scientific domains based on the cocitation of classes and categories," Scientometrics, Springer;Akadémiai Kiadó, vol. 61(1), pages 129-145, September.
    26. van Eck, N.J.P. & Waltman, L., 2009. "VOSviewer: A Computer Program for Bibliometric Mapping," ERIM Report Series Research in Management ERS-2009-005-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    27. Loet Leydesdorff & Ismael Rafols, 2009. "A global map of science based on the ISI subject categories," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 348-362, February.
    28. Ed C. M. Noyons & Clara Calero-Medina, 2009. "Applying bibliometric mapping in a high level science policy context," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(2), pages 261-275, May.
    29. Loet Leydesdorff, 2007. "Betweenness centrality as an indicator of the interdisciplinarity of scientific journals," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(9), pages 1303-1319, July.
    30. Waltman, Ludo & van Eck, Nees Jan & Noyons, Ed C.M., 2010. "A unified approach to mapping and clustering of bibliometric networks," Journal of Informetrics, Elsevier, vol. 4(4), pages 629-635.
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    Cited by:

    1. Karimi, Fatemeh & Lotfi, Shahriar & Izadkhah, Habib, 2021. "Community-guided link prediction in multiplex networks," Journal of Informetrics, Elsevier, vol. 15(4).
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    3. Tian, Yunpei & Li, Gang & Mao, Jin, 2023. "Predicting the evolution of scientific communities by interpretable machine learning approaches," Journal of Informetrics, Elsevier, vol. 17(2).
    4. Wu, Yujia & Lan, Wei & Fan, Xinyan & Fang, Kuangnan, 2024. "Bipartite network influence analysis of a two-mode network," Journal of Econometrics, Elsevier, vol. 239(2).

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