IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v126y2021i6d10.1007_s11192-021-03963-6.html
   My bibliography  Save this article

Evolutionary exploration and comparative analysis of the research topic networks in information disciplines

Author

Listed:
  • Xiaoguang Wang

    (Wuhan University)

  • Hongyu Wang

    (Wuhan University
    The University of Texas at Austin)

  • Han Huang

    (Wuhan University)

Abstract

“Information Science and Library Science” (LIS) and “Computer Science” (CS) are two information-related disciplines with similar academic context and culture, and their research topics are moderately associated. To uncover the differences and similarities of their research topics in the aspect of dynamic distribution, and explore the future development state of relevant research, this study collected a set of scientific papers from 2014 to 2019 on the Web of Science to construct the co-keyword network sequences for the disciplines of LIS and CS respectively. The networking topology and evolutionary context of research topics in recent research of these two information-related disciplines were analyzed through a self-developed visualization tool for network evolution analysis—NEViewer. This study suggests that CS pays more attention to the studies of information technologies, while LIS focuses more on the communication, organization, access, and use of information. Meanwhile, based on the perspective of discipline-comparative, the development patterns in these two disciplines were summarized. That is, the research connotation of CS is more concentrated while the research denotation of LIS is more extensive, and the research hotspots of LIS have shifted slightly faster, while the continuity of the research development in CS is slightly higher. The results reported in this study also show that there is moderate interdisciplinarity in the research and application of information technology between these two disciplines, which indicates that some increasingly mature technologies in CS will be more deeply applied in the future research of LIS.

Suggested Citation

  • Xiaoguang Wang & Hongyu Wang & Han Huang, 2021. "Evolutionary exploration and comparative analysis of the research topic networks in information disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4991-5017, June.
  • Handle: RePEc:spr:scient:v:126:y:2021:i:6:d:10.1007_s11192-021-03963-6
    DOI: 10.1007/s11192-021-03963-6
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-021-03963-6
    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/s11192-021-03963-6?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. Mu-hsuan Huang & Wang-Ching Shaw & Chi-Shiou Lin, 2019. "One category, two communities: subfield differences in “Information Science and Library Science” in Journal Citation Reports," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1059-1079, May.
    2. Chang-Ping Hu & Ji-Ming Hu & Sheng-Li Deng & Yong Liu, 2013. "A co-word analysis of library and information science in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 369-382, November.
    3. Vincent Larivière & Cassidy R. Sugimoto & Blaise Cronin, 2012. "A bibliometric chronicling of library and information science's first hundred years," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(5), pages 997-1016, May.
    4. Shino Iwami & Arto Ojala & Chihiro Watanabe & Pekka Neittaanmäki, 2020. "A bibliometric approach to finding fields that co-evolved with information technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 3-21, January.
    5. Guo Chen & Lu Xiao & Chang-ping Hu & Xue-qin Zhao, 2015. "Identifying the research focus of Library and Information Science institutions in China with institution-specific keywords," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 707-724, May.
    6. Erjia Yan & Jake Williams & Zheng Chen, 2017. "Understanding disciplinary vocabularies using a full-text enabled domain-independent term extraction approach," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-16, November.
    7. González-Albo, Borja & Bordons, María, 2011. "Articles vs. proceedings papers: Do they differ in research relevance and impact? A case study in the Library and Information Science field," Journal of Informetrics, Elsevier, vol. 5(3), pages 369-381.
    8. Xiaoyao Han, 2020. "Evolution of research topics in LIS between 1996 and 2019: an analysis based on latent Dirichlet allocation topic model," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2561-2595, December.
    9. Yu-Wei Chang, 2018. "Examining interdisciplinarity of library and information science (LIS) based on LIS articles contributed by non-LIS authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1589-1613, September.
    10. Yu-Wei Chang & Mu-Hsuan Huang & Chiao-Wen Lin, 2015. "Evolution of research subjects in library and information science based on keyword, bibliographical coupling, and co-citation analyses," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 2071-2087, December.
    11. Danielle H. Lee, 2019. "Predicting the research performance of early career scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1481-1504, December.
    12. Xie, Yundong & Wu, Qiang & Zhang, Peng & Li, Xingchen, 2020. "Information Science and Library Science (IS-LS) journal subject categorisation and comparison based on editorship information," Journal of Informetrics, Elsevier, vol. 14(4).
    13. Gao-Yong Liu & Ji-Ming Hu & Hui-Ling Wang, 2012. "A co-word analysis of digital library field in China," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(1), pages 203-217, April.
    14. Sitaram Devarakonda & Dmitriy Korobskiy & Tandy Warnow & George Chacko, 2020. "Viewing computer science through citation analysis: Salton and Bergmark Redux," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 271-287, October.
    15. Johann Bauer & Loet Leydesdorff & Lutz Bornmann, 2016. "Highly cited papers in Library and Information Science (LIS): Authors, institutions, and network structures," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(12), pages 3095-3100, December.
    16. Xie, Qing & Zhang, Xinyuan & Ding, Ying & Song, Min, 2020. "Monolingual and multilingual topic analysis using LDA and BERT embeddings," Journal of Informetrics, Elsevier, vol. 14(3).
    17. Yan Yan & Zhewen Liao & Xiaosong Chen, 2018. "Fixed-income securities: bibliometric review with network analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1615-1640, September.
    18. William H. Walters & Esther Isabelle Wilder, 2016. "Disciplinary, national, and departmental contributions to the literature of library and information science, 2007–2012," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(6), pages 1487-1506, June.
    19. Yongjun Zhu & Erjia Yan & Min Song, 2016. "Understanding the evolving academic landscape of library and information science through faculty hiring data," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1461-1478, September.
    20. Tanmoy Chakraborty, 2018. "Role of interdisciplinarity in computer sciences: quantification, impact and life trajectory," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1011-1029, March.
    21. Maja Jokić, 2020. "Productivity, visibility, authorship, and collaboration in library and information science journals: Central and Eastern European authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1189-1219, February.
    22. Sung Kim & Derek Hansen & Richard Helps, 2018. "Computing research in the academy: insights from theses and dissertations," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(1), pages 135-158, January.
    23. Otto Tuomaala & Kalervo Järvelin & Pertti Vakkari, 2014. "Evolution of library and information science, 1965–2005: Content analysis of journal articles," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 65(7), pages 1446-1462, July.
    24. Tsung-Ming Hsiao & Kuang-hua Chen, 2020. "The dynamics of research subfields for library and information science: an investigation based on word bibliographic coupling," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 717-737, October.
    25. Pin Li & Guoli Yang & Chuanqi Wang, 2019. "Visual topical analysis of library and information science," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1753-1791, December.
    26. Ping Liu & Qiong Wu & Xiangming Mu & Kaipeng Yu & Yiting Guo, 2015. "Detecting the intellectual structure of library and information science based on formal concept analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 737-762, September.
    27. Vincent Larivière & Cassidy R. Sugimoto & Blaise Cronin, 2012. "A bibliometric chronicling of library and information science's first hundred years," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(5), pages 997-1016, May.
    28. Yu-Wei Chang & Mu-Hsuan Huang, 2012. "A study of the evolution of interdisciplinarity in library and information science: Using three bibliometric methods," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(1), pages 22-33, January.
    29. Yu‐Wei Chang & Mu‐Hsuan Huang, 2012. "A study of the evolution of interdisciplinarity in library and information science: Using three bibliometric methods," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(1), pages 22-33, January.
    30. Xiaoguang Wang & Qikai Cheng & Wei Lu, 2014. "Analyzing evolution of research topics with NEViewer: a new method based on dynamic co-word networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1253-1271, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Urdiales, Cristina & Guzmán, Eduardo, 2024. "An automatic and association-based procedure for hierarchical publication subject categorization," Journal of Informetrics, Elsevier, vol. 18(1).
    2. Kaiwen Shi & Kan Liu & Xinyan He, 2024. "Heterogeneous hypergraph learning for literature retrieval based on citation intents," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 4167-4188, July.
    3. Wang, Xiaoguang & He, Jing & Huang, Han & Wang, Hongyu, 2022. "MatrixSim: A new method for detecting the evolution paths of research topics," Journal of Informetrics, Elsevier, vol. 16(4).
    4. Katchanov, Yurij L. & Markova, Yulia V., 2022. "Dynamics of senses of new physics discourse: Co-keywords analysis," Journal of Informetrics, Elsevier, vol. 16(1).

    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. Abhijit Thakuria & Dipen Deka, 2024. "A decadal study on identifying latent topics and research trends in open access LIS journals using topic modeling approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(7), pages 3841-3869, July.
    2. Yu-Wei Chang, 2018. "Examining interdisciplinarity of library and information science (LIS) based on LIS articles contributed by non-LIS authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(3), pages 1589-1613, September.
    3. Cristóbal Urbano & Jordi Ardanuy, 2020. "Cross-disciplinary collaboration versus coexistence in LIS serials: analysis of authorship affiliations in four European countries," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 575-602, July.
    4. Ping Liu & Qiong Wu & Xiangming Mu & Kaipeng Yu & Yiting Guo, 2015. "Detecting the intellectual structure of library and information science based on formal concept analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 737-762, September.
    5. Pertti Vakkari & Yu-Wei Chang & Kalervo Järvelin, 2022. "Largest contribution to LIS by external disciplines as measured by the characteristics of research articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4499-4522, August.
    6. Wang, Xiaoguang & He, Jing & Huang, Han & Wang, Hongyu, 2022. "MatrixSim: A new method for detecting the evolution paths of research topics," Journal of Informetrics, Elsevier, vol. 16(4).
    7. Carlos Olmeda-Gómez & Maria-Antonia Ovalle-Perandones & Antonio Perianes-Rodríguez, 2017. "Co-word analysis and thematic landscapes in Spanish information science literature, 1985–2014," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 195-217, October.
    8. Yu-Wei Chang, 2019. "Are articles in library and information science (LIS) journals primarily contributed to by LIS authors?," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 81-104, October.
    9. Yuen-Hsien Tseng & Ming-Yueh Tsay, 2013. "Journal clustering of library and information science for subfield delineation using the bibliometric analysis toolkit: CATAR," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 503-528, May.
    10. Pertti Vakkari & Yu‐Wei Chang & Kalervo Järvelin, 2022. "Disciplinary contributions to research topics and methodology in Library and Information Science—Leading to fragmentation?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(12), pages 1706-1722, December.
    11. Sümeyye Akça & Özlem Şenyurt, 2023. "Geographical representation of editorial boards: a review in the field of library and information sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(2), pages 1409-1427, February.
    12. Maja Jokić, 2020. "Productivity, visibility, authorship, and collaboration in library and information science journals: Central and Eastern European authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1189-1219, February.
    13. Min Song & Go Eun Heo & Su Yeon Kim, 2014. "Analyzing topic evolution in bioinformatics: investigation of dynamics of the field with conference data in DBLP," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 397-428, October.
    14. Jingjing Ren & Fang Wang & Minglu Li, 2023. "Dynamics and characteristics of interdisciplinary research in scientific breakthroughs: case studies of Nobel-winning research in the past 120 years," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4383-4419, August.
    15. Xiaoyao Han, 2020. "Evolution of research topics in LIS between 1996 and 2019: an analysis based on latent Dirichlet allocation topic model," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2561-2595, December.
    16. Jian Xu & Yi Bu & Ying Ding & Sinan Yang & Hongli Zhang & Chen Yu & Lin Sun, 2018. "Understanding the formation of interdisciplinary research from the perspective of keyword evolution: a case study on joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 973-995, November.
    17. María Pinto & Rosaura Fernández-Pascual & David Caballero-Mariscal & Dora Sales, 2020. "Information literacy trends in higher education (2006–2019): visualizing the emerging field of mobile information literacy," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1479-1510, August.
    18. A. Velez-Estevez & P. García-Sánchez & J. A. Moral-Munoz & M. J. Cobo, 2022. "Why do papers from international collaborations get more citations? A bibliometric analysis of Library and Information Science papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7517-7555, December.
    19. Pertti Vakkari & Kalervo Järvelin & Yu‐Wei Chang, 2023. "The association of disciplinary background with the evolution of topics and methods in Library and Information Science research 1995–2015," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(7), pages 811-827, July.
    20. Mu-hsuan Huang & Wang-Ching Shaw & Chi-Shiou Lin, 2019. "One category, two communities: subfield differences in “Information Science and Library Science” in Journal Citation Reports," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1059-1079, May.

    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_s11192-021-03963-6. 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.