Characterizing References from Different Disciplines: A Perspective of Citation Content Analysis

Multidisciplinary cooperation is now common in research since social issues inevitably involve multiple disciplines. In research articles, reference information, especially citation content, is an important representation of communication among different disciplines. Analyzing the distribution characteristics of references from different disciplines in research articles is basic to detecting the sources of referred information and identifying contributions of different disciplines. This work takes articles in PLoS as the data and characterizes the references from different disciplines based on Citation Content Analysis (CCA). First, we download 210,334 full-text articles from PLoS and collect the information of the in-text citations. Then, we identify the discipline of each reference in these academic articles. To characterize the distribution of these references, we analyze three characteristics, namely, the number of citations, the average cited intensity and the average citation length. Finally, we conclude that the distributions of references from different disciplines are significantly different. Although most references come from Natural Science, Humanities and Social Sciences play important roles in the Introduction and Background sections of the articles. Basic disciplines, such as Mathematics, mainly provide research methods in the articles in PLoS. Citations mentioned in the Results and Discussion sections of articles are mainly in-discipline citations, such as citations from Nursing and Medicine in PLoS.

[1]  R. Kirk.  Practical Significance: A Concept Whose Time Has Come , 1996 .

[2]  Jagoda Spaventi,et al.  Citation Context Versus the Frequency Counts of Citation Histories , 1998, J. Am. Soc. Inf. Sci..

[3]  Daqing He,et al.  Global health crises are also information crises: A call to action , 2020, J. Assoc. Inf. Sci. Technol..

[4]  Lydia L. Lange,et al.  Effects of disciplines and countries on citation habits. An analysis of empirical papers in behavioural sciences , 1985, Scientometrics.

[5]  Qiao Li,et al.  The preferences of Chinese LIS journal articles in citing works outside the discipline , 2018, J. Documentation.

[6]  Hai Zhuge,et al.  Discovery of knowledge flow in science , 2006, CACM.

[7]  Staša Milojević,et al.  Citation content analysis (CCA): A framework for syntactic and semantic analysis of citation content , 2012, J. Assoc. Inf. Sci. Technol..

[8]  Chengzhi Zhang,et al.  Examining similarities and differences of citation patterns between monographs and papers: a case in biology and computer science , 2019 .

[9]  Henry Voos,et al.  Are All Citations Equal? Or, Did We Op. Cit. Your Idem?. , 1976 .

[10]  Xiaojun Wan,et al.  WL‐index: Leveraging citation mention number to quantify an individual's scientific impact , 2014, J. Assoc. Inf. Sci. Technol..

[11]  Saeed-Ul Hassan,et al.  A novel machine-learning approach to measuring scientific knowledge flows using citation context analysis , 2018, Scientometrics.

[12]  Jeffrey C. Stier,et al.  The impact of interdisciplinary research in the environmental sciences: a forestry case study , 2000, Journal of the American Society for Information Science.

[13]  Albert-László Barabási,et al.  Nature’s reach: narrow work has broad impact , 2019, Nature.

[14]  M. Thelwall.  Should Citations be Counted Separately from Each Originating Section , 2019, J. Informetrics.

[15]  Juan Gorraiz,et al.  Reference density trends in the major disciplines , 2018, J. Informetrics.

[16]  Vincent Larivière,et al.  The invariant distribution of references in scientific articles , 2016, J. Assoc. Inf. Sci. Technol..

[17]  Guo Zhang,et al.  Content‐based citation analysis: The next generation of citation analysis , 2014, J. Assoc. Inf. Sci. Technol..

[18]  Chengzhi Zhang,et al.  What type of domain knowledge is cited by articles with high interdisciplinary degree? , 2018, ASIST.

[19]  Peter Haddawy,et al.  Analyzing knowledge flows of scientific literature through semantic links: a case study in the field of energy , 2015, Scientometrics.

[20]  Peter Willett,et al.  Quantifying the value of knowledge exports from librarianship and information science research , 2013, J. Inf. Sci..

[21]  Henk F. Moed,et al.  The thematic and conceptual flow of disciplinary research: A citation context analysis of the journal of informetrics, 2007 , 2013, J. Assoc. Inf. Sci. Technol..

[22]  Qiao Li,et al.  The impact of Chinese library and information science on outside disciplines: A citation analysis , 2020, J. Libr. Inf. Sci..

[23]  Ying Ding,et al.  The distribution of references across texts: Some implications for citation analysis , 2013, J. Informetrics.

[24]  Daryl E. Chubin,et al.  Content Analysis of References: Adjunct or Alternative to Citation Counting? , 1975 .

[25]  Thed N. van Leeuwen,et al.  Measuring knowledge transfer between fields of science , 2002, Scientometrics.

[26]  Kevin W. Boyack,et al.  Characterizing in-text citations in scientific articles: A large-scale analysis , 2017, J. Informetrics.

[27]  Gabriel Pinski,et al.  Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics , 1976, Inf. Process. Manag..

[28]  Hyun Woo Park,et al.  Patterns of scientific and technological knowledge flows based on scientific papers and patents , 2009, Scientometrics.

[29]  Henry M. Kim,et al.  Information Systems is Not a Reference Discipline (And What We Can Do About It) , 2006, J. Assoc. Inf. Syst..

[30]  Enrique Vidal,et al.  Computation of Normalized Edit Distance and Applications , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[31]  Katherine W. McCain,et al.  Citation context analysis and aging patterns of journal articles in molecular genetics , 1989, Scientometrics.

[32]  Marc Bertin,et al.  InTeReC: In-text Reference Corpus for Applying Natural Language Processing to Bibliometrics , 2018, BIR@ECIR.

[33]  Michael H. MacRoberts,et al.  Problems of citation analysis , 1996, Scientometrics.

[34]  Charles Oppenheim,et al.  Highly cited old papers and the reasons why they continue to be cited , 1978, J. Am. Soc. Inf. Sci..

[35]  Claudio Castellano,et al.  Universality of citation distributions: Toward an objective measure of scientific impact , 2008, Proceedings of the National Academy of Sciences.

[36]  Eugene Garfield,et al.  Is citation analysis a legitimate evaluation tool? , 2005, Scientometrics.