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The proximity of co-citation

Author

Listed:
  • Shengbo Liu

    (Dalian University of Technology)

  • Chaomei Chen

    (Drexel University)

Abstract

Traditional co-citation analysis has not taken the proximity of co-cited references into account. As long as two references are cited by the same article, they are retreated equally regardless the distance between where citations appear in the article. Little is known about what additional insights into citation and co-citation behaviours one might gain from studying distributions of co-citation in terms of such proximity. How are citations distributed in an article? What insights does the proximity of co-citation provide? In this article, the proximity of a pair of co-cited reference is defined as the nearest instance of the co-citation relation in text. We investigate the proximity of co-citation in full text of scientific publications at four levels, namely, the sentence level, the paragraph level, the section level, and the article level. We conducted four studies of co-citation patterns in the full text of articles published in 22 open access journals from BioMed Central. First, we compared the distributions of co-citation instances at four proximity levels in journal articles to the traditional article-level co-citation counts. Second, we studied the distributions of co-citations of various proximities across organizational sections in articles. Third, the distribution of co-citation proximity in different co-citation frequency groups is investigated. Fourth, we identified the occurrences of co-citations at different proximity levels with reference to the corresponding traditional co-citation network. The results show that (1) the majority of co-citations are loosely coupled at the article level, (2) a higher proportion of sentence-level co-citations is found in high co-citation frequencies than in low co-citation frequencies, (3) tightly coupled sentence-level co-citations not only preserve the essential structure of the corresponding traditional co-citation network but also form a much smaller subset of the entire co-citation instances typically considered by traditional co-citation analysis. Implications for improving our understanding of underlying factors concerning co-citations and developing more efficient co-citation analysis methods are discussed.

Suggested Citation

  • Shengbo Liu & Chaomei Chen, 2012. "The proximity of co-citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 495-511, May.
    • Handle: RePEc:spr:scient:v:91:y:2012:i:2:d:10.1007_s11192-011-0575-7
    DOI: 10.1007/s11192-011-0575-7
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    References listed on IDEAS

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    Cited by:

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    3. Raja Habib & Muhammad Tanvir Afzal, 2019. "Sections-based bibliographic coupling for research paper recommendation," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 643-656, May.
    4. Hua Li & Weijun Wang, 2022. "Knowledge Domain and Emerging Trends of Social Vulnerability Research: A Bibliometric Analysis (1991–2021)," IJERPH, MDPI, vol. 19(14), pages 1-15, July.
    5. Kamal Sanguri & Atanu Bhuyan & Sabyasachi Patra, 2020. "A semantic similarity adjusted document co-citation analysis: a case of tourism supply chain," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 233-269, October.
    6. Moshe Blidstein & Maayan Zhitomirsky-Geffet, 2022. "Towards a new generic framework for citation network generation and analysis in the humanities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4275-4297, July.
    7. Annarelli, Alessandro & Battistella, Cinzia & Nonino, Fabio & Parida, Vinit & Pessot, Elena, 2021. "Literature review on digitalization capabilities: Co-citation analysis of antecedents, conceptualization and consequences," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    8. Lijun Yang & Liangxiu Han & Naxin Liu, 2019. "A new approach to journal co-citation matrix construction based on the number of co-cited articles in journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(2), pages 507-517, August.
    9. Marc Bertin & Iana Atanassova & Cassidy R. Sugimoto & Vincent Lariviere, 2016. "The linguistic patterns and rhetorical structure of citation context: an approach using n-grams," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1417-1434, December.
    10. Bikun Chen & Dannan Deng & Zhouyan Zhong & Chengzhi Zhang, 2020. "Exploring linguistic characteristics of highly browsed and downloaded academic articles," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(3), pages 1769-1790, March.
    11. Kim, Ha Jin & Jeong, Yoo Kyung & Song, Min, 2016. "Content- and proximity-based author co-citation analysis using citation sentences," Journal of Informetrics, Elsevier, vol. 10(4), pages 954-966.
    12. Dangzhi Zhao & Andreas Strotmann, 2020. "Telescopic and panoramic views of library and information science research 2011–2018: a comparison of four weighting schemes for author co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 255-270, July.
    13. Jun Gao & Muhammad Faheem & Xiang Yu, 2022. "Global Research on Contaminated Soil Remediation: A Bibliometric Network Analysis," Land, MDPI, vol. 11(9), pages 1-16, September.
    14. Boutheina Fhoula & Majed Hadid & Adel Elomri & Laoucine Kerbache & Anas Hamad & Mohammed Hamad J. Al Thani & Raed M. Al-Zoubi & Abdulla Al-Ansari & Omar M. Aboumarzouk & Abdelfatteh El Omri, 2022. "Home Cancer Care Research: A Bibliometric and Visualization Analysis (1990–2021)," IJERPH, MDPI, vol. 19(20), pages 1-25, October.
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