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Why words and co‐words cannot map the development of the sciences

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  • Loet Leydesdorff

Abstract

A restricted set of full‐text articles from a sub‐specialty of biochemistry was analyzed and compared in terms of co‐occurrences and co‐absences of words. By using the distribution of words over the sections, a clear distinction among “theoretical” “observational,” and “methodological” terminology can be made in individual articles. However, at the level of the set this structure is no longer retrievable: Words change both in terms of frequencies of relations with other words, and in terms of positional meaning from one text to another. These results accord with Hesse's (1980) thesis about the sciences as fluid networks. The fluidity of networks in which nodes and links may change positions is expected to destabilize representations of developments of the sciences on the basis of co‐occurrences and co‐absences of words. The consequences for the lexicographical approach to generating artificial intelligence from scientific texts are discussed. © 1997 John Wiley & Sons, Inc.

Suggested Citation

  • Loet Leydesdorff, 1997. "Why words and co‐words cannot map the development of the sciences," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 48(5), pages 418-427, May.
  • Handle: RePEc:bla:jamest:v:48:y:1997:i:5:p:418-427
    DOI: 10.1002/(SICI)1097-4571(199705)48:53.0.CO;2-Y
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    1. Guillermo Armando Ronda-Pupo & Luis Ángel Guerras-Martín, 2010. "Dynamics of the scientific community network within the strategic management field through the Strategic Management Journal 1980–2009: the role of cooperation," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 821-848, December.
    2. Yating Zhao & Jingjing Guo & Chao Bao & Changyong Liang & Hemant K Jain, 2020. "Knowledge Graph Analysis of Human Health Research Related to Climate Change," IJERPH, MDPI, vol. 17(20), pages 1-19, October.
    3. Koondhar, Mansoor Ahmed & Shahbaz, Muhammad & Memon, Kamran Ali & Ozturk, Ilhan & Rong, Kong, 2020. "A visualization review analysis of the last two decades for Environmental Kuznets Curve “EKC” based on co-citation analysis theory and pathfinder network scaling algorithms," MPRA Paper 104949, University Library of Munich, Germany, revised 18 Dec 2020.
    4. Mora, Luca & Deakin, Mark & Reid, Alasdair, 2019. "Combining co-citation clustering and text-based analysis to reveal the main development paths of smart cities," Technological Forecasting and Social Change, Elsevier, vol. 142(C), pages 56-69.
    5. Staša Milojević & Cassidy R. Sugimoto & Erjia Yan & Ying Ding, 2011. "The cognitive structure of Library and Information Science: Analysis of article title words," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 62(10), pages 1933-1953, October.
    6. Chaoqun Ni & Cassidy R. Sugimoto & Jiepu Jiang, 2013. "Venue-author-coupling: A measure for identifying disciplines through author communities," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(2), pages 265-279, February.
    7. Mark William Neff & Elizabeth A. Corley, 2009. "35 years and 160,000 articles: A bibliometric exploration of the evolution of ecology," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(3), pages 657-682, September.
    8. Mike Thelwall & Pardeep Sud, 2021. "Do new research issues attract more citations? A comparison between 25 Scopus subject categories," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(3), pages 269-279, March.
    9. M. Angeles Zulueta & Gisela Cantos-Mateos & Benjamín Vargas-Quesada & Carmen Sánchez, 2011. "Research involving women and health in the Medline database, 1965–2005: co-term analysis and visualization of main lines of research," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(3), pages 679-706, September.
    10. Peter Mutschke & Anabel Quan Haase, 2001. "Collaboration and Cognitive Structures in Social Science Research Fields. Towards Socio-Cognitive Analysis in Information Systems," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(3), pages 487-502, November.
    11. Burmaoglu, Serhat & Sartenaer, Olivier & Porter, Alan, 2019. "Conceptual definition of technology emergence: A long journey from philosophy of science to science policy," Technology in Society, Elsevier, vol. 59(C).
    12. Leydesdorff, Loet & Welbers, Kasper, 2011. "The semantic mapping of words and co-words in contexts," Journal of Informetrics, Elsevier, vol. 5(3), pages 469-475.
    13. Gaston Heimeriks & Ron Boschma, 2014. "The path- and place-dependent nature of scientific knowledge production in biotech 1986–2008," Journal of Economic Geography, Oxford University Press, vol. 14(2), pages 339-364.
    14. Qiang Yao & Peng-Hui Lyu & Lian-Ping Yang & Lan Yao & Zhi-Yong Liu, 2014. "Current performance and future trends in health care sciences and services research," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 751-779, October.
    15. Christian Weismayer & Ilona Pezenka, 2017. "Identifying emerging research fields: a longitudinal latent semantic keyword analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1757-1785, December.
    16. Peng Hui Lv & Gui-Fang Wang & Yong Wan & Jia Liu & Qing Liu & Fei-cheng Ma, 2011. "Bibliometric trend analysis on global graphene research," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(2), pages 399-419, August.
    17. Camille Prime & Elise Bassecoulard & Michel Zitt, 2002. "Co-citations and co-sitations: A cautionary view on an analogy," Scientometrics, Springer;Akadémiai Kiadó, vol. 54(2), pages 291-308, June.
    18. Chaoqun Ni & Cassidy R. Sugimoto & Blaise Cronin, 2013. "Visualizing and comparing four facets of scholarly communication: producers, artifacts, concepts, and gatekeepers," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1161-1173, March.
    19. Loet Leydesdorff, 2013. "Statistics for the dynamic analysis of scientometric data: the evolution of the sciences in terms of trajectories and regimes," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(3), pages 731-741, September.
    20. Victor Rodriguez & Frizo Janssens & Koenraad Debackere & Bart Moor, 2007. "Do material transfer agreements affect the choice of research agendas? The case of biotechnology in Belgium," Scientometrics, Springer;Akadémiai Kiadó, vol. 71(2), pages 239-269, May.
    21. Topalli, Margerita & Ivanaj, Silvester, 2016. "Mapping the evolution of the impact of economic transition on Central and Eastern European enterprises: A co-word analysis," Journal of World Business, Elsevier, vol. 51(5), pages 744-759.
    22. Bo Wang & Shengbo Liu & Kun Ding & Zeyuan Liu & Jing Xu, 2014. "Identifying technological topics and institution-topic distribution probability for patent competitive intelligence analysis: a case study in LTE technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 685-704, October.
    23. Rons, Nadine, 2018. "Bibliometric approximation of a scientific specialty by combining key sources, title words, authors and references," Journal of Informetrics, Elsevier, vol. 12(1), pages 113-132.

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