IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v83y2010i3d10.1007_s11192-009-0149-0.html
   My bibliography  Save this article

Rete-netzwerk-red: analyzing and visualizing scholarly networks using the Network Workbench Tool

Author

Listed:
  • Katy Börner

    (Indiana University)

  • Weixia Huang

    (Indiana University)

  • Micah Linnemeier

    (Indiana University)

  • Russell J. Duhon

    (Indiana University)

  • Patrick Phillips

    (Indiana University)

  • Nianli Ma

    (Indiana University)

  • Angela M. Zoss

    (Indiana University)

  • Hanning Guo

    (Indiana University)

  • Mark A. Price

    (Indiana University)

Abstract

The enormous increase in digital scholarly data and computing power combined with recent advances in text mining, linguistics, network science, and scientometrics make it possible to scientifically study the structure and evolution of science on a large scale. This paper discusses the challenges of this ‘BIG science of science’—also called ‘computational scientometrics’ research—in terms of data access, algorithm scalability, repeatability, as well as result communication and interpretation. It then introduces two infrastructures: (1) the Scholarly Database (SDB) ( http://sdb.slis.indiana.edu ), which provides free online access to 22 million scholarly records—papers, patents, and funding awards which can be cross-searched and downloaded as dumps, and (2) Scientometrics-relevant plug-ins of the open-source Network Workbench (NWB) Tool ( http://nwb.slis.indiana.edu ). The utility of these infrastructures is then exemplarily demonstrated in three studies: a comparison of the funding portfolios and co-investigator networks of different universities, an examination of paper-citation and co-author networks of major network science researchers, and an analysis of topic bursts in streams of text. The article concludes with a discussion of related work that aims to provide practically useful and theoretically grounded cyberinfrastructure in support of computational scientometrics research, education and practice.

Suggested Citation

  • Katy Börner & Weixia Huang & Micah Linnemeier & Russell J. Duhon & Patrick Phillips & Nianli Ma & Angela M. Zoss & Hanning Guo & Mark A. Price, 2010. "Rete-netzwerk-red: analyzing and visualizing scholarly networks using the Network Workbench Tool," Scientometrics, Springer;Akadémiai Kiadó, vol. 83(3), pages 863-876, June.
    • Handle: RePEc:spr:scient:v:83:y:2010:i:3:d:10.1007_s11192-009-0149-0
    DOI: 10.1007/s11192-009-0149-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-009-0149-0
    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/s11192-009-0149-0?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. Chaomei Chen, 2006. "CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 57(3), pages 359-377, February.
    2. Lokman I. Meho & Kiduk Yang, 2007. "Impact of data sources on citation counts and rankings of LIS faculty: Web of science versus scopus and google scholar," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(13), pages 2105-2125, November.
    3. Gavin LaRowe & Sumeet Ambre & John Burgoon & Weimao Ke & Katy Börner, 2009. "The Scholarly Database and its utility for scientometrics research," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(2), pages 219-234, May.
    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. Zhao, Star X. & Rousseau, Ronald & Ye, Fred Y., 2011. "h-Degree as a basic measure in weighted networks," Journal of Informetrics, Elsevier, vol. 5(4), pages 668-677.
    2. Juan Ruiz-Rosero & Gustavo Ramirez-Gonzalez & Jesus Viveros-Delgado, 2019. "Software survey: ScientoPy, a scientometric tool for topics trend analysis in scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 1165-1188, November.
    3. Cynthia W. Cai & Martina K. Linnenluecke & Mauricio Marrone & Abhay K. Singh, 2019. "Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific," Abacus, Accounting Foundation, University of Sydney, vol. 55(4), pages 709-733, December.
    4. 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.
    5. Feng Hu & Wei Liu & Sang-Bing Tsai & Junbin Gao & Ning Bin & Quan Chen, 2018. "An Empirical Study on Visualizing the Intellectual Structure and Hotspots of Big Data Research from a Sustainable Perspective," Sustainability, MDPI, vol. 10(3), pages 1-19, March.
    6. Chenjia Zhang & Yiping Fang & Xiujuan Chen & Tian Congshan, 2019. "Bibliometric Analysis of Trends in Global Sustainable Livelihood Research," Sustainability, MDPI, vol. 11(4), pages 1-28, February.
    7. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.

    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. Francisco Díez-Martín & Alicia Blanco-González & Camilo Prado-Román, 2021. "The intellectual structure of organizational legitimacy research: a co-citation analysis in business journals," Review of Managerial Science, Springer, vol. 15(4), pages 1007-1043, May.
    2. Muaz Niazi & Amir Hussain, 2011. "Agent-based computing from multi-agent systems to agent-based models: a visual survey," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 479-499, November.
    3. Hao Tan & Yuyue Hao, 2022. "Mapping the Global Evolution and Research Directions of Information Seeking, Sharing and Communication in Disasters: A Bibliometric Study," IJERPH, MDPI, vol. 19(22), pages 1-20, November.
    4. Yue Guiling & Siti Aisyah Panatik & Mohammad Saipol Mohd Sukor & Noraini Rusbadrol & Li Cunlin, 2022. "Bibliometric Analysis of Global Research on Organizational Citizenship Behavior From 2000 to 2019," SAGE Open, , vol. 12(1), pages 21582440221, February.
    5. Hugo Baier-Fuentes & José M. Merigó & José Ernesto Amorós & Magaly Gaviria-Marín, 2019. "International entrepreneurship: a bibliometric overview," International Entrepreneurship and Management Journal, Springer, vol. 15(2), pages 385-429, June.
    6. Seyedghorban, Zahra & Matanda, Margaret Jekanyika & LaPlaca, Peter, 2016. "Advancing theory and knowledge in the business-to-business branding literature," Journal of Business Research, Elsevier, vol. 69(8), pages 2664-2677.
    7. Feng Hu & Wei Liu & Sang-Bing Tsai & Junbin Gao & Ning Bin & Quan Chen, 2018. "An Empirical Study on Visualizing the Intellectual Structure and Hotspots of Big Data Research from a Sustainable Perspective," Sustainability, MDPI, vol. 10(3), pages 1-19, March.
    8. Izaskun Alvarez-Meaza & Enara Zarrabeitia-Bilbao & Rosa Maria Rio-Belver & Gaizka Garechana-Anacabe, 2020. "Fuel-Cell Electric Vehicles: Plotting a Scientific and Technological Knowledge Map," Sustainability, MDPI, vol. 12(6), pages 1-25, March.
    9. Yubin Qian & Ya Sun, 2022. "Bibliometric analysis of literature on narrative discourse in corporate annual reports (1990–2019)," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(2), pages 429-446, April.
    10. McLevey, John & McIlroy-Young, Reid, 2017. "Introducing metaknowledge: Software for computational research in information science, network analysis, and science of science," Journal of Informetrics, Elsevier, vol. 11(1), pages 176-197.
    11. Tingcan Ma & Ruinan Li & Guiyan Ou & Mingliang Yue, 2018. "Topic based research competitiveness evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 789-803, November.
    12. Jacob Wood & Gohar Feroz Khan, 2015. "International trade negotiation analysis: network and semantic knowledge infrastructure," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 537-556, October.
    13. Lakshmi Balachandran Nair & Michael Gibbert, 2016. "What makes a ‘good’ title and (how) does it matter for citations? A review and general model of article title attributes in management science," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(3), pages 1331-1359, June.
    14. Daniel Fonseca Costa & Francisval Carvalho & Bruno César Moreira & José Willer Prado, 2017. "Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1775-1799, June.
    15. Xingwen Chen & Li Zhu & Chao Liu & Chunhua Chen & Jun Liu & Dongxia Huo, 2023. "Workplace Diversity in the Asia-Pacific Region: A Review of Literature and Directions for Future Research," Asia Pacific Journal of Management, Springer, vol. 40(3), pages 1021-1045, September.
    16. Ziwen Wei & Man Yuan, 2023. "Research on the Current Situation and Future Development Trend of Immersive Virtual Reality in the Field of Education," Sustainability, MDPI, vol. 15(9), pages 1-18, May.
    17. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.
    18. 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.
    19. Petersen, Alexander M. & Rotolo, Daniele & Leydesdorff, Loet, 2016. "A triple helix model of medical innovation: Supply, demand, and technological capabilities in terms of Medical Subject Headings," Research Policy, Elsevier, vol. 45(3), pages 666-681.
    20. Tong Chen & Mo Wang & Jin Su & Jianjun Li, 2023. "Unlocking the Positive Impact of Bio-Swales on Hydrology, Water Quality, and Biodiversity: A Bibliometric Review," Sustainability, MDPI, vol. 15(10), pages 1-19, 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:83:y:2010:i:3:d:10.1007_s11192-009-0149-0. 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.