IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v126y2021i6d10.1007_s11192-021-03959-2.html
   My bibliography  Save this article

RelPath: an interactive tool to visualize branches of studies and quantify the expertise of authors by citation paths

Author

Listed:
  • Orlando Fonseca Guilarte

    (Pontifical Catholic University of Rio de Janeiro)

  • Simone Diniz Junqueira Barbosa

    (Pontifical Catholic University of Rio de Janeiro)

  • Sinesio Pesco

    (Pontifical Catholic University of Rio de Janeiro)

Abstract

Networks of scientific publications play a fundamental role in the search for relevant papers to a specific research topic, as well as in finding authors with expertise in different branches of study. Making a selection of the most important references of a specific paper to understand the evolution of a branch of study is an essential task in the academic world. A challenge for the scientific community has been to identify possible authors relevant to a target paper, for example, to select them as potential reviewers. A solution to find potential expert candidates can be based on the network of citations and on how relevant the authors of selecting papers are in relation to the target paper. With the motivation for developing interactive visual software that helps both researchers and editorial committees, in this paper we present RelPath, a system to help with the task of finding relevant papers and authors for a selected paper. RelPath includes the submission paper in a citations network and establishes relevance of the edges in the network, through which it is possible to build branches of studies and establish a ranking of authors. In this work, we introduce an index to quantify the expertise of the authors by citation paths and we propose a collaborative method to ranking references.

Suggested Citation

  • Orlando Fonseca Guilarte & Simone Diniz Junqueira Barbosa & Sinesio Pesco, 2021. "RelPath: an interactive tool to visualize branches of studies and quantify the expertise of authors by citation paths," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4871-4897, June.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:6:d:10.1007_s11192-021-03959-2
    DOI: 10.1007/s11192-021-03959-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-021-03959-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-021-03959-2?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dangzhi Zhao & Andreas Strotmann, 2020. "Deep and narrow impact: introducing location filtered citation counting," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 503-517, January.
    2. Michaël Charles Waumans & Hugues Bersini, 2016. "Genealogical Trees of Scientific Papers," PLOS ONE, Public Library of Science, vol. 11(3), pages 1-15, March.
    3. Kevin W. Boyack & Richard Klavans, 2014. "Creation of a highly detailed, dynamic, global model and map of science," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(4), pages 670-685, April.
    4. Xiaodan Zhu & Peter Turney & Daniel Lemire & André Vellino, 2015. "Measuring academic influence: Not all citations are equal," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(2), pages 408-427, February.
    5. Nadia Simoes & Nuno Crespo, 2020. "A flexible approach for measuring author-level publishing performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 331-355, January.
    6. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    7. Shutian Ma & Chengzhi Zhang & Xiaozhong Liu, 2020. "A review of citation recommendation: from textual content to enriched context," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1445-1472, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Naif Radi Aljohani & Ayman Fayoumi & Saeed-Ul Hassan, 2021. "An in-text citation classification predictive model for a scholarly search system," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5509-5529, July.
    2. Zhang, Fang & Wu, Shengli, 2020. "Predicting future influence of papers, researchers, and venues in a dynamic academic network," Journal of Informetrics, Elsevier, vol. 14(2).
    3. Xie, Qing & Zhang, Xinyuan & Song, Min, 2021. "A network embedding-based scholar assessment indicator considering four facets: Research topic, author credit allocation, field-normalized journal impact, and published time," Journal of Informetrics, Elsevier, vol. 15(4).
    4. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    5. Zhaoping Yan & Kaiyu Fan, 2024. "An integrated indicator for evaluating scientific papers: considering academic impact and novelty," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(11), pages 6909-6929, November.
    6. Weibin Wang & Zheng Wang & Tian Yu & CholMyong Pak & Guang Yu, 2020. "Research on citation mention times and contributions using a neural network," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2383-2400, December.
    7. Fang Zhang & Shengli Wu, 2021. "Measuring academic entities’ impact by content-based citation analysis in a heterogeneous academic network," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7197-7222, August.
    8. Christin Katharina Kreutz & Premtim Sahitaj & Ralf Schenkel, 2020. "Evaluating semantometrics from computer science publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2915-2954, December.
    9. Ruijie Wang & Yuhao Zhou & An Zeng, 2023. "Evaluating scientists by citation and disruption of their representative works," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1689-1710, March.
    10. Dongqing Lyu & Xuanmin Ruan & Juan Xie & Ying Cheng, 2021. "The classification of citing motivations: a meta-synthesis," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 3243-3264, April.
    11. Maor Weinberger & Maayan Zhitomirsky-Geffet, 2021. "Diversity of success: measuring the scholarly performance diversity of tenured professors in the Israeli academia," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(4), pages 2931-2970, April.
    12. Shengzhi Huang & Jiajia Qian & Yong Huang & Wei Lu & Yi Bu & Jinqing Yang & Qikai Cheng, 2022. "Disclosing the relationship between citation structure and future impact of a publication," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(7), pages 1025-1042, July.
    13. Carlos Olmeda-Gómez & Carlos Romá-Mateo & Maria-Antonia Ovalle-Perandones, 2019. "Overview of trends in global epigenetic research (2009–2017)," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1545-1574, June.
    14. Sehrish Iqbal & Saeed-Ul Hassan & Naif Radi Aljohani & Salem Alelyani & Raheel Nawaz & Lutz Bornmann, 2021. "A decade of in-text citation analysis based on natural language processing and machine learning techniques: an overview of empirical studies," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6551-6599, August.
    15. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    16. Gaviria-Marin, Magaly & Merigó, José M. & Baier-Fuentes, Hugo, 2019. "Knowledge management: A global examination based on bibliometric analysis," Technological Forecasting and Social Change, Elsevier, vol. 140(C), pages 194-220.
    17. Faiza Qayyum & Harun Jamil & Naeem Iqbal & DoHyeun Kim & Muhammad Tanvir Afzal, 2022. "Toward potential hybrid features evaluation using MLP-ANN binary classification model to tackle meaningful citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6471-6499, November.
    18. David L. Anderson & John Tressler, 2013. "The Relevance of the “h-” and “g-” Index to Economics in the Context of A Nation-Wide Research Evaluation Scheme: The New Zealand Case," Economic Papers, The Economic Society of Australia, vol. 32(1), pages 81-94, March.
    19. Marek Kwiek & Wojciech Roszka, 2022. "Academic vs. biological age in research on academic careers: a large-scale study with implications for scientifically developing systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3543-3575, June.
    20. Ash Mohammad Abbas, 2011. "Weighted indices for evaluating the quality of research with multiple authorship," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(1), pages 107-131, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:126:y:2021:i:6:d:10.1007_s11192-021-03959-2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.