This article gives an overview of co-citation analysis and its applications in tracking the linkages among the intellectual works and mapping the evolutionary structure of scientific disciplines. It also focuses on the features, interface, terminology used, merits and demerits of co-citation based online database applications

Bhanumurthy, K.

Kademani, B. S.

Sagar, Anil

Surwase, G.

English

E-LIS

 Co-citation Analysis: An Overview   Ganesh Surwase, Anil Sagar, B. S. Kademani and K. Bhanumurthy Scientific Information Resource Division, Bhabha Atomic Research Centre, Trombay, Mumbai (India) - 400085. surwaseg@barc.gov.in  This article gives an overview of co-citation analysis and its applications in tracking the linkages among the intellectual works and mapping the evolutionary structure of scientific disciplines. It also focuses on the features, interface, terminology used, merits and demerits of co-citation based online database applications.  Keywords: Co-citation analysis, intellectual linkages, structure of science, SciVal Spotlight   1. INTRODUCTION Today’s advanced scientific knowledge is the cumulative effect of earlier research works. Each research paper reference/cite to the earlier research paper. In another way, each current paper is an extension of earlier research topic. Thus the intellectual linkages are established between the previous and current research topics. Knowledge is multidimensional, multifaceted, multidirectional and interdisciplinary in nature growing at a faster pace. It is essential to classify the knowledge to understand the growth and evolution in a better way. There are various methods of knowledge classification developed over a period of time. Co-citation analysis is one of the most effective and efficient methods of knowledge mapping. Many attempts have been made in the past manually to understand the structure of knowledge in a limited way. The advances in computer and information technology and developments of well-structured databases has paved way for co-citation applications.  Classification of research article based on the journal is too general or vague, because each scientific journal is classified into a major field despite the fact that journals are progressively covering a wider array of disciplines and paradigms. Co-citation analysis, involves classifying the scientific literature into small groups of papers that correspond to specific problems. Henry Small, known as father of co-citation analysis applied the technique to identify the strengths and weaknesses of an institution.   2. BIBLIOGRAPHIC COUPLING VS CO-CITATION COUPLING The term ‘bibliographic coupling’ was first introduced by M.M. Kessler in 1963. Bibliographic coupling occurs when two works reference a common third work in their bibliographies. The bibliographic coupling strength increases with the increase in the number of references they have in common. Bibliographic coupling is used to extrapolate how similar the subject matter of the two works is. Bibliographic coupling is not subjectively valuable in all fields of research since it helps the researcher to find related research done in the past.  BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings)  Co-citation Analysis: An Overview               180   In 1973 Henry Small introduced the term concept of co-citation analysis, as a better indicator of subject similarity. Co-citation coupling is a method used to establish a subject similarity between two documents. The two documents are said to be co-cited when they both appear in the reference list of a third document. If papers A and B are both cited by paper C, they may be said to be related to one another, even though they don't directly cite each other. If papers A and B are both cited by many other papers, they have a stronger relationship. The more papers they are cited by, the stronger their relationship is. The co-citation frequency is defined as the frequency with which two documents are cited together. Figure-1 illustrates the concept of bibliographic coupling and co-citation coupling.     Figure-1: Bibliographic coupling and co-citation coupling  3. CO-CITATION ANALYSIS In bibliometrics, there have been extensive studies on the assessment of document similarities. For instance, Kessler proposed the approach of bibliographic coupling, and Small proposed the co-citation approach. The purpose for the assessment of document similarities is to classify documents. The classified levels include the document itself, its author, and the journal that contains the document.   Documents co-citation is used to conduct searches on similar documents. Journal co-citation is of interest to the collection manager concerned with developing core journal lists, selecting journals and evaluating collections that serve particular research-oriented constituencies. Author co-citation analysis has been used in analyzing the intellectual structure of scientific disciplines.  Co-citation analysis is a unique method for studying the cognitive structure of science. Co-citation analysis involves tracking pairs of papers that are cited together in the source articles. When the same pairs of papers are co-cited by many authors, clusters of research begin to form. The co-cited papers in these clusters tend to share some common theme. Combined with single-link clustering and multidimensional scaling techniques, co-citation analysis can literally map the structure of specialized research areas as well as science as a whole.   BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings)  Co-citation Analysis: An Overview               181  Co-citation analysis creates paradigms/ clusters to reveal interdisciplinary research trends within institutions. The ideas of co-citation have been applied to commercial application such as SciVal Spotlight etc. It is one of the most effective methods of monitoring the development and structure of science.   4. APPLICATION OF CO-CITATION ANALYSIS - SCIVAL SPOTLIGHT SciVal Spotlight is a web-based application brought out by Elsevier Publishers. It is based on the technique of co-citation analysis. In SciVal Spotlight the articles cited for a year are clustered into two groups:  1. Highly cited reference articles for the map year are selected and clustered based on co-citation counts.  2. Current articles are assigned to the clusters based on their references. These current articles can be fractionally assigned to the clusters based on the distribution of their references.   Co-citation clusters are thus comprised of reference articles and the current articles that cite them. Each cluster is assigned to a discipline or subject area. It uses ccommercial online bibliographic database (Scopus) to retrieve the co-citation frequency matrix.  Steps involved in the generating the results and maps by SciVal Spotlight are as follows: 1: Selecting the publications: SciVal Spotlight uses one year of publications in order to pick up current trends.  2: Selecting the references: SciVal Spotlight’s threshold for highly cited references is 5 to 100 citations, and threshold for papers those published 4 years ago is age of paper + 1 citation.  3: Calculating the relatedness between these references: generate cocitation clusters by using a modified cosine index based on co-citation counts for similarity, and run the resulting matrix of cosine values through a visualization program (DrL) which would assign each reference paper an (x, y) position on a 2-D plane. Visualization program ‘DrL’ is a force directed placement algorithm with edge cutting, it acts as a filter that reduces the inherent noise in the system  4: Clustering the references: SciVal Spotlight’s average-link clustering algorithm is used to cluster the (x, y) positional data output of the DrL layout algorithm.  5: Assigning current papers to these clusters: Each current paper is assigned fractionally to clusters based on the references in the paper. SciVal Spotlight also assigns the four previous years of current papers to the reference structure identified above. This allows one to identify publications trends associated with a specific set of highly cited references.  In SciVal Spotlight the proprietary algorithm is run on the data produced by co-citation counts and the result, graphs and maps are displayed.   BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings)  Co-citation Analysis: An Overview               182  5. INTERFACE OF SCIVAL SPOTLIGHT The screenshots of various functions of SciVal Spotlight are given below:       BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings)  Co-citation Analysis: An Overview               183      6. TERMINOLOGY USED IN SCIVAL SPOTLIGHT Competencies: A competency is a network of article clusters that are grouped together. If an institute is #1 or #2 in either RAS, RRS or SotA, it forms competency.   Distinctive Competency (DC): It is the subject area where an institute has a large relative market share compared to peers active in that same subject area. In order for a competency to become a distinctive competency market size shall be ≥ 200articles and the institute must be leader in either publication, reference or state of the art.  BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings)  Co-citation Analysis: An Overview               184   Emerging Competency (EC): It is the competency where your institute is not number 1 but it hold the potential to be #1.   Highly Cited References: Threshold for highly cited references is5 to 100 citations for the articles older than 5 years and article’s age + a citation for the articles not older than 5 years. Maximum 100 citations are considered to avoid the aggregation effect.   Market Size: The total number of articles in each competency, not just from an Institute but from all institutes in that region which contribute to this competency. The values are fractionalized, meaning that only the fraction of each article that falls within the competency is counted.   Growth Rate: It is nothing but the average yearly change in the number of articles within each competency from all institutions in the given region. The average growth is calculated from pairs of subsequent years. The two year part is formed by adding two subsequent years, then slide to the next year and calculate the growth.   Relative Article Share (RAS): RAS means how many articles within each competency are from Institute relative to the institution ranked #1 in that competency. If Institute is ranked #1, the value is compared to the institution ranked #2.   Relative Reference Share (RRS): Relative Reference Share (RRS): The number of highly cited reference articles that are authored Institute divided by that of the institute ranked #1 in that competency. If Institute is ranked #1, the value is compared to the institution ranked #2.   State of the Art (SotA): The recency of the work cited by the articles from an institute within each competency, relative to the average recency for that competency. Positive values indicate the work being cited is more recent than average. Example: If SotA value for Institute is 5, it means references cited by Institute are 5 years recent than the average recency of the competency.   Subject Area: It is a graphical representation of the primary subject areas of each article cluster within the competency. There are 13 primary subject areas comprised of 566 minor subject categories. High-level competencies are formed by merging low level competencies for each of the primary subject areas.   Rank: The rank of an Institute within each competency, calculated over the entire 5-year period. Relative Article Share (RAS) determines the rank of an institution in the competency.   7. MERITS OF SCIVAL SPOTLIGHT This co-citation based web application ‘SciVal Spotlight’ map the knowledge at interdisciplinary levels. It helps to accommodate scarce resources and reduce organisational in-efficiencies. Also helps to identify specific areas of research excellence, emerging competencies. Identify potential collaborating authors/ institutions. It enables to find out the leading researchers/experts/peers in various fields. One can compare the results with other competing institutions/authors. It helps to review competitive standings of an institute on a global scale.  BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings)  Co-citation Analysis: An Overview               185  8. DEMERITS/ LIMITATIONS OF SCIVAL SPOTLIGHT SciVal Spotlight is database dependent and it carries forward the shortcomings and limitations of source (Scopus) database like literature coverage, input time lag, variations in name of author, institute etc. The maps generated are not clearly understandable (less expressive). In this proprietary application, data is hidden and just results are shown. Categorisation and numbering of competencies is not in a specific order. Average recency (RAS) in terms of number of years, is relative i.e. less interpretative. With the help of SciVal Spotlight the publication list for an author/ institution can not be generated.  9. CONCLUSION Co-citation analysis based applications encourage researchers to explore the intellectual structure of science and guide them about the future developments. Intellectual linkages are established through the process of referencing and citation. It is a research tool for examining the intellectual development and structure of the scientific discipline.   REFERENCES 1. Co-Citation Analysis: The Methodology of SciVal Spotlight http://www.americalatina.elsevier.com/sul/pt-br/scival/pdf/Co-Citation_Analysis_SciVal_ Spotlight.pdf 2. Culnan, Mary J. 1987. Mapping the intellectual structure of MIS, 1980-1985: A co-citation analysis. MIS Quarterly, 11(3), pp. 341-353.  3. Eom, Sean B. 1996. Mapping the intellectual structure of research in decision support systems through author co-citation analysis (1971-1993). Decision Support Systems, 16(4), pp. 315-338. 4. Kessler, M. M. 1963. Bibliographic coupling between scientific papers. American Documentation, 14(1), pp. 10-25.  5. McCain, K. W. 1986. Co-cited author mapping as a valid representation of intellectual structure. Journal of the American Society for Information Science, 37(3), pp. 111-122.  6. McCain, K. W. 1990. Mapping authors in intellectual space: a technical overview. Journal of the American Society for Information Science, 41(6), pp. 433-443.  7. Small, H. 1973. Cocitation in scientific literature: New measure of relationship between two documents. Journal of the American Society for Information Science, 24(4), 265-269.  8. Small, H. 1999.Visualizing science by citation mapping. Journal of the American Society for Information Science, 50(9), 799-813.  9. Small, H. 2003. Paradigms, citations and maps of science: A personal history. Journal of the American Society for Information Science and Technology, 54(5), 394-399.  10. White, H. D. and Griffith, B. C. 1981. Author co-citation: a literature measure of intellectual structure. Journal of the American Society for Information Science, 32, pp. 163-171.  

1999.Visualizing science by citation mapping.

Author co-citation: a literature measure of intellectual structure.

Bibliographic coupling between scientific papers.

Co-Citation Analysis: The Methodology of SciVal Spotlight

Co-cited author mapping as a valid representation of intellectual structure.

Cocitation in scientific literature: New measure of relationship between two documents.

Mapping authors in intellectual space: a technical overview.

Mapping the intellectual structure of MIS, 1980-1985: A co-citation analysis.

Mapping the intellectual structure of research in decision support systems through author co-citation analysis (1971-1993).

Paradigms, citations and maps of science: A personal history.

Co-citation Analysis: An Overview

E-LIS repository

 
Co-citation Analysis: An Overview 
 
 
Ganesh Surwase, Anil Sagar, B. S. Kademani and K. Bhanumurthy 
Scientific Information Resource Division, Bhabha Atomic Research Centre, 
Trombay, Mumbai (India) - 400085. surwaseg@barc.gov.in 
 
This article gives an overview of co-citation analysis and its applications in 
tracking the linkages among the intellectual works and mapping the 
evolutionary structure of scientific disciplines. It also focuses on the features, 
interface, terminology used, merits and demerits of co-citation based online 
database applications. 
 
Keywords: Co-citation analysis, intellectual linkages, structure of science, 
SciVal Spotlight 
 
 
1. INTRODUCTION 
Today’s advanced scientific knowledge is the cumulative effect of earlier research works. Each 
research paper reference/cite to the earlier research paper. In another way, each current paper is 
an extension of earlier research topic. Thus the intellectual linkages are established between the 
previous and current research topics. Knowledge is multidimensional, multifaceted, 
multidirectional and interdisciplinary in nature growing at a faster pace. It is essential to classify 
the knowledge to understand the growth and evolution in a better way. There are various 
methods of knowledge classification developed over a period of time. Co-citation analysis is one 
of the most effective and efficient methods of knowledge mapping. Many attempts have been 
made in the past manually to understand the structure of knowledge in a limited way. The 
advances in computer and information technology and developments of well-structured 
databases has paved way for co-citation applications. 
 
Classification of research article based on the journal is too general or vague, because each 
scientific journal is classified into a major field despite the fact that journals are progressively 
covering a wider array of disciplines and paradigms. Co-citation analysis, involves classifying 
the scientific literature into small groups of papers that correspond to specific problems. Henry 
Small, known as father of co-citation analysis applied the technique to identify the strengths and 
weaknesses of an institution.  
 
2. BIBLIOGRAPHIC COUPLING VS CO-CITATION COUPLING 
The term ‘bibliographic coupling’ was first introduced by M.M. Kessler in 1963. Bibliographic 
coupling occurs when two works reference a common third work in their bibliographies. The 
bibliographic coupling strength increases with the increase in the number of references they have 
in common. Bibliographic coupling is used to extrapolate how similar the subject matter of the 
two works is. Bibliographic coupling is not subjectively valuable in all fields of research since it 
helps the researcher to find related research done in the past.  
BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings) 
 
Co-citation Analysis: An Overview               180 
 
 
In 1973 Henry Small introduced the term concept of co-citation analysis, as a better indicator of 
subject similarity. Co-citation coupling is a method used to establish a subject similarity between 
two documents. The two documents are said to be co-cited when they both appear in the 
reference list of a third document. If papers A and B are both cited by paper C, they may be said 
to be related to one another, even though they don't directly cite each other. If papers A and B are 
both cited by many other papers, they have a stronger relationship. The more papers they are 
cited by, the stronger their relationship is. The co-citation frequency is defined as the frequency 
with which two documents are cited together. Figure-1 illustrates the concept of bibliographic 
coupling and co-citation coupling.  
 
 
 
Figure-1: Bibliographic coupling and co-citation coupling 
 
3. CO-CITATION ANALYSIS 
In bibliometrics, there have been extensive studies on the assessment of document similarities. 
For instance, Kessler proposed the approach of bibliographic coupling, and Small proposed the 
co-citation approach. The purpose for the assessment of document similarities is to classify 
documents. The classified levels include the document itself, its author, and the journal that 
contains the document.  
 
Documents co-citation is used to conduct searches on similar documents. Journal co-citation is of 
interest to the collection manager concerned with developing core journal lists, selecting journals 
and evaluating collections that serve particular research-oriented constituencies. Author co-
citation analysis has been used in analyzing the intellectual structure of scientific disciplines. 
 
Co-citation analysis is a unique method for studying the cognitive structure of science. Co-
citation analysis involves tracking pairs of papers that are cited together in the source articles. 
When the same pairs of papers are co-cited by many authors, clusters of research begin to form. 
The co-cited papers in these clusters tend to share some common theme. Combined with single-
link clustering and multidimensional scaling techniques, co-citation analysis can literally map the 
structure of specialized research areas as well as science as a whole.  
 
BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings) 
 
Co-citation Analysis: An Overview               181 
 
Co-citation analysis creates paradigms/ clusters to reveal interdisciplinary research trends within 
institutions. The ideas of co-citation have been applied to commercial application such as SciVal 
Spotlight etc. It is one of the most effective methods of monitoring the development and structure 
of science.  
 
4. APPLICATION OF CO-CITATION ANALYSIS - SCIVAL SPOTLIGHT 
SciVal Spotlight is a web-based application brought out by Elsevier Publishers. It is based on the 
technique of co-citation analysis. In SciVal Spotlight the articles cited for a year are clustered 
into two groups: 
 
1. Highly cited reference articles for the map year are selected and clustered based on co-citation 
counts.  
2. Current articles are assigned to the clusters based on their references. These current articles 
can be fractionally assigned to the clusters based on the distribution of their references.  
 
Co-citation clusters are thus comprised of reference articles and the current articles that cite 
them. Each cluster is assigned to a discipline or subject area. It uses ccommercial online 
bibliographic database (Scopus) to retrieve the co-citation frequency matrix. 
 
Steps involved in the generating the results and maps by SciVal Spotlight are as follows: 
1: Selecting the publications: SciVal Spotlight uses one year of publications in order to pick up 
current trends. 
 
2: Selecting the references: SciVal Spotlight’s threshold for highly cited references is 5 to 100 
citations, and threshold for papers those published 4 years ago is age of paper + 1 citation. 
 
3: Calculating the relatedness between these references: generate cocitation clusters by using 
a modified cosine index based on co-citation counts for similarity, and run the resulting matrix of 
cosine values through a visualization program (DrL) which would assign each reference paper an 
(x, y) position on a 2-D plane. Visualization program ‘DrL’ is a force directed placement 
algorithm with edge cutting, it acts as a filter that reduces the inherent noise in the system 
 
4: Clustering the references: SciVal Spotlight’s average-link clustering algorithm is used to 
cluster the (x, y) positional data output of the DrL layout algorithm. 
 
5: Assigning current papers to these clusters: Each current paper is assigned fractionally to 
clusters based on the references in the paper. SciVal Spotlight also assigns the four previous 
years of current papers to the reference structure identified above. This allows one to identify 
publications trends associated with a specific set of highly cited references. 
 
In SciVal Spotlight the proprietary algorithm is run on the data produced by co-citation counts 
and the result, graphs and maps are displayed. 
  
BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings) 
 
Co-citation Analysis: An Overview               182 
 
5. INTERFACE OF SCIVAL SPOTLIGHT 
The screenshots of various functions of SciVal Spotlight are given below: 
 
 
 
 
 
 
BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings) 
 
Co-citation Analysis: An Overview               183 
 
 
 
 
 
6. TERMINOLOGY USED IN SCIVAL SPOTLIGHT 
Competencies: A competency is a network of article clusters that are grouped together. If an 
institute is #1 or #2 in either RAS, RRS or SotA, it forms competency.  
 Distinctive Competency (DC): It is the subject area where an institute has a large relative 
market share compared to peers active in that same subject area. In order for a competency 
to become a distinctive competency market size shall be ≥ 200articles and the institute must 
be leader in either publication, reference or state of the art.  
BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings) 
 
Co-citation Analysis: An Overview               184 
 
 Emerging Competency (EC): It is the competency where your institute is not number 1 but it 
hold the potential to be #1.  
 
Highly Cited References: Threshold for highly cited references is5 to 100 citations for the 
articles older than 5 years and article’s age + a citation for the articles not older than 5 years. 
Maximum 100 citations are considered to avoid the aggregation effect.  
 
Market Size: The total number of articles in each competency, not just from an Institute but from 
all institutes in that region which contribute to this competency. The values are fractionalized, 
meaning that only the fraction of each article that falls within the competency is counted.  
 
Growth Rate: It is nothing but the average yearly change in the number of articles within each 
competency from all institutions in the given region. The average growth is calculated from pairs 
of subsequent years. The two year part is formed by adding two subsequent years, then slide to 
the next year and calculate the growth.  
 
Relative Article Share (RAS): RAS means how many articles within each competency are from 
Institute relative to the institution ranked #1 in that competency. If Institute is ranked #1, the 
value is compared to the institution ranked #2.  
 
Relative Reference Share (RRS): Relative Reference Share (RRS): The number of highly cited 
reference articles that are authored Institute divided by that of the institute ranked #1 in that 
competency. If Institute is ranked #1, the value is compared to the institution ranked #2.  
 
State of the Art (SotA): The recency of the work cited by the articles from an institute within 
each competency, relative to the average recency for that competency. Positive values indicate 
the work being cited is more recent than average. Example: If SotA value for Institute is 5, it 
means references cited by Institute are 5 years recent than the average recency of the 
competency.  
 
Subject Area: It is a graphical representation of the primary subject areas of each article cluster 
within the competency. There are 13 primary subject areas comprised of 566 minor subject 
categories. High-level competencies are formed by merging low level competencies for each of 
the primary subject areas.  
 
Rank: The rank of an Institute within each competency, calculated over the entire 5-year period. 
Relative Article Share (RAS) determines the rank of an institution in the competency.  
 
7. MERITS OF SCIVAL SPOTLIGHT 
This co-citation based web application ‘SciVal Spotlight’ map the knowledge at interdisciplinary 
levels. It helps to accommodate scarce resources and reduce organisational in-efficiencies. Also 
helps to identify specific areas of research excellence, emerging competencies. Identify potential 
collaborating authors/ institutions. It enables to find out the leading researchers/experts/peers in 
various fields. One can compare the results with other competing institutions/authors. It helps to 
review competitive standings of an institute on a global scale. 
 
BEYOND LIBRARIANSHIP: Creativity, Innovation and Discovery (BOSLA National Conference Proceedings) 
 
Co-citation Analysis: An Overview               185 
 
8. DEMERITS/ LIMITATIONS OF SCIVAL SPOTLIGHT 
SciVal Spotlight is database dependent and it carries forward the shortcomings and limitations of 
source (Scopus) database like literature coverage, input time lag, variations in name of author, 
institute etc. The maps generated are not clearly understandable (less expressive). In this 
proprietary application, data is hidden and just results are shown. Categorisation and numbering 
of competencies is not in a specific order. Average recency (RAS) in terms of number of years, 
is relative i.e. less interpretative. With the help of SciVal Spotlight the publication list for an 
author/ institution can not be generated. 
 
9. CONCLUSION 
Co-citation analysis based applications encourage researchers to explore the intellectual structure 
of science and guide them about the future developments. Intellectual linkages are established 
through the process of referencing and citation. It is a research tool for examining the intellectual 
development and structure of the scientific discipline.  
 
REFERENCES 
1. Co-Citation Analysis: The Methodology of SciVal Spotlight 
http://www.americalatina.elsevier.com/sul/pt-br/scival/pdf/Co-Citation_Analysis_SciVal_ 
Spotlight.pdf 
2. Culnan, Mary J. 1987. Mapping the intellectual structure of MIS, 1980-1985: A co-citation 
analysis. MIS Quarterly, 11(3), pp. 341-353.  
3. Eom, Sean B. 1996. Mapping the intellectual structure of research in decision support 
systems through author co-citation analysis (1971-1993). Decision Support Systems, 16(4), 
pp. 315-338. 
4. Kessler, M. M. 1963. Bibliographic coupling between scientific papers. American 
Documentation, 14(1), pp. 10-25.  
5. McCain, K. W. 1986. Co-cited author mapping as a valid representation of intellectual 
structure. Journal of the American Society for Information Science, 37(3), pp. 111-122.  
6. McCain, K. W. 1990. Mapping authors in intellectual space: a technical overview. Journal of 
the American Society for Information Science, 41(6), pp. 433-443.  
7. Small, H. 1973. Cocitation in scientific literature: New measure of relationship between two 
documents. Journal of the American Society for Information Science, 24(4), 265-269.  
8. Small, H. 1999.Visualizing science by citation mapping. Journal of the American Society for 
Information Science, 50(9), 799-813.  
9. Small, H. 2003. Paradigms, citations and maps of science: A personal history. Journal of the 
American Society for Information Science and Technology, 54(5), 394-399.  
10. White, H. D. and Griffith, B. C. 1981. Author co-citation: a literature measure of intellectual 
structure. Journal of the American Society for Information Science, 32, pp. 163-171.  


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Co-citation Analysis: An Overview

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