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Are Scientometrics, Informetrics, and Bibliometrics different?

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Siluo Yang at Wuhan University
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Bibliometrics, scientometrics, and informetrics (also called the three metrics) differ in subject background but are the same in theories, methods, technologies, and applications. Analyzing their current situation and relationships can help comprehensively understand the three fields. In this study, we collect the data of the three metrics through keyword search in 2007–2016. We also compare and visualize the three metrics in terms of the distribution of publications and cooperation (recognition level), the main research topics (intellectual structure), and the reference situation (knowledge communication). Results show that the three metrics differ in the degrees of utilization and recognition but are similar in the general direction. We recommend the addition of bibliometrics in the title of the International Society for Scientometrics and Informetrics.
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TYPE：Full Paper
Are Scientometrics, Informetrics, and Bibliometrics different?
Yang Siluo1 and Yuan Qingli2
1 58605025@qq.com
Wuhan University, Wuhan (China)
2 331061947@qq.com
Wuhan University, Wuhan (China)
Abstract
Bibliometrics, scientometrics, and informetrics (also called the three metrics) differ in subject background but
are the same in theories, methods, technologies, and applications. Analyzing their current situation and
relationships can help comprehensively understand the three fields. In this study, we collect the data of the three
metrics through keyword search in 2007–2016. We also compare and visualize the three metrics in terms of the
distribution of publications and cooperation (recognition level), the main research topics (intellectual structure),
and the reference situation (knowledge communication). Results show that the three metrics differ in the degrees
of utilization and recognition but are similar in the general direction. We recommend the addition of
bibliometrics in the title of the International Society for Scientometrics and Informetrics.
Keywords
Bibliometrics; Scientometrics; Informetrics; Knowledge Domain Visualization; CiteSpace
Conference Topic
The relationship and development of five metric science concepts: Bibliometrics, Informetrics, Scientometrics,
Webometrics, and Knowledgometrics.
Introduction
Bibliometrics, scientometrics, and informetrics (also called the three metrics) are three related
terms in metrology. These terms are used to describe similar and overlapping methodologies;
however, their well-documented historical origins differ, and they are not necessarily
synonymous (Hood & Wilson, 2001). The rapid progress and development of science and
technology have improved the research objects, goals, and methods of the three metrics. New
branches such as webmetrics and altmetrics (Egghe, 2005), and new indexes and evaluation
measures including Citescore and the H index, have also appeared (Hirsch, 2005). Although
these terms differ in disciplinary background and emergence time (Qiu et al., 2017), they are
used in accordance with their own cognition and position, thereby causing significant
confusion. There are many journals with “scientometrics” or “informetrics” in their titles exist,
but few journals with “bibliometrics” in their titles exist. The International Society for
Scientometrics and Informetrics (ISSI) is the most significant conference in the three metrics.
ISSI contains scientometrics and informetrics in its title but has no bibliometrics. Given that
confusion can harm the development and application of the three metrics (Hood & Wilson,
2001), the development of the three terms and their relationships should be examined. This
study explores the current situation and relationships of the three metrics from the following
three aspects: the number of published papers and cooperation (recognition level), the main
research topics (intellectual structure), and the reference situation (knowledge
communication).
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Background
Definitions of bibliometrics
Bibliometrics methods have been applied in various forms for more than a century (Hood &
Wilson, 2001). The term “bibliometrics” was first introduced by Pritchard (1969), who
defined it as “the application of mathematical and statistical methods to books and other
media of communication.” Fairthorne (1969) expanded the definition scope of bibliometrics
by defining it as the quantitative treatment of the properties of recorded discourse and
behavior appertaining to it. Then, Broadus (1987) defined bibliometrics as the quantitative
study of physically published units, or of bibliographic units, or of alternatives of either.
Definitions of scientometrics
Nalimov and Mulchenko (1971) coined the Russian equivalent of the term “scientometrics” in
1969, and defined it as the quantitative study of various kinds of intelligence process in the
development of science. The term has obtained broad acceptance from the journal
Scientometrics, which was built in 1978. Scientometrics is a discipline that uses mathematical
methods to quantify the scientific research personnel and achievements to reveal the process
of scientific development, and can provide scientific basis for scientific decision making and
management (Qiu et al., 2017). Scientometrics uses citation analysis and other quantitative
methods to evaluate scientific research activities and thus guide the policy of science (Egghe,
2005).
Definitions of informetrics
Nacke first proposed the German term “informetrie.” By the early 1990s, the term
“informetrics” obtained wide recognition. Nacke believed that informetrics is a study applied
in mathematical methods for information science objects (Qiu et al., 2017). This definition is
slightly one sided because it limits the scope of informetrics in information science. Tague-
Sutcliffe extended informetrics to the quantitative study of any form of information; thus,
informetrics is not simply a bibliographic record or any social group, or not limited to
scientists (Fairthorne, 1969). This definition enlarges the research scope and content of
informetrics. Qiu et al. (2017) divided informetrics into two aspects of broad and narrow
senses. The broad sense of informetrics research is very broad, whereas the narrow sense of
informetrics mainly uses mathematical, statistical, and other quantitative methods to study the
characteristics and laws of information quantitatively.
Relationships among the three metrics
The three terms have evolved to share many of the objectives and have many methods and
tools in common (Qiu et al., 2017). The three metrics refer to “component fields related to the
study of the dynamics of disciplines as reflected in the production of their literature” (Hood &
Wilson, 2001). The three terms often appear simultaneously, or used interchangeably by
authors, such as the Second International Conference on Bibliometrics, Scientometrics, and
Informetrics (now called “ISSI”). However, the terms differ in their discipline attribute;
specifically, bibliometrics belongs to library and document science, scientometrics belongs to
the science of science, and informetrics belongs to information science (Brookes, 1990; Qiu et
al., 2017; Wang, 1998). Scientometrics and informetrics have been proposed for nearly 50 and
40 years, respectively; however, they lack their own uniform concepts that can be widely
accepted by the public. Different definitions of bibliometrics also exist (Hood & Wilson,
2001).
The relationship among the three metrics has long been investigated. Brooks (1990) explored
the origin and interrelationship of the three metrics. Glänzel and Schoepflin (1994)
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emphasized that the authors’ use of “bibliometrics” synonymously for the three metrics has
resulted in chaos. Hood and Wilson (2001) analyzed the differences among the three metrics
by investigating the history of the three terms through analyzing the number of papers and
journals between 1968 and 2000. Wen and Qiu (2006) suggested that the three metrics belong
to different superordinate disciplines; however, they have the same research objects,
indicators, and methods. Some believed that the three metrics present a crossing and partial
overlapping relationship, but others argued that the three metrics exhibit an inclusive
relationship; for example, informetrics has many meanings and includes bibliometrics and
scientometrics (Qiu et al., 2017)
Data and method
A subject or discipline is often analyzed using the literature statistics, which accesses data
samples in two ways: (1) choosing the top journals or core journals in the field as the data
source (Milojevic & Leydesdorff, 2013), and (2) obtaining data source through the retrieval of
representative keywords (Hood & Wilson, 2001). The journals in the three metrics present
great repeatability and are widely distributed. Thus, this study uses keyword research to
obtain data for the comprehensive comparison of the differences among the three metrics.
Method
The current situation and relationships of the three metrics include various aspects. In this
study, we analyze only three major areas: 1) the usage and distribution of the three terms on
the basis of the number of publications and cooperation; 2) the research contents and
intellectual structure on the basis of field topics; and 3) the knowledge communication and
flow on the basis of the citation and reference. We use EXCEL and CiteSpace for data
statistics and network development .
Data
We downloaded data sets comprising articles, reviews, and papers from SCI-Expanded, SSCI,
and A&HCI between 2007 and 2016. Following Hood and Wilson (2001), we retrieve the
literature of the three metrics using “TS = (bibliometric* or bibliometry or bibliometrical* or
bibliometrician* or “statistical bibliography” or bibliometrie),” “TS = (scientometric* or
scientometry or scientometrical* or scientometrician*),” and “TS = (informetric* or
informetry or informetrician* or informetrie).” Finally, we combine the three search strategies
to investigate the overlapping situation of the three metrics.
Result
Overall situation
The retrieval results show that bibliometrics has the largest number of publications, which is
approximately four times of that of scientometrics and 20 times of that of informetrics. A
large difference is found in the number of literature among the three fields in 2007–2016,
possibly because of the difference in their history and degree of social recognition. In the past
10 years, the annual volume of publications on bibliometrics is higher than that on
scientometrics and informetrics, the number of publications on bibliometrics has the largest
increase among the three fields, the increase for scientometrics is at an intermediate level and
informetrics presents the smallest increase .
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Figure 1 Search results of combining the three metrics
Distribution of publications and cooperation
Number of publications in different levels
The European countries dominate more than half of the top 10 national rankings of the three
metrics, indicating that Europe is the core area of international research on the three metrics.
Europe is the origin of the three fields and has a long history of research; thus, it is home to
popular research institutions and experts. With regard to American countries, the United
States and Brazil as the main country, the number of publications in the field of bibliometrics
and scientometrics are higher than informetrics. Scientometrics has been widely explored and
is highly recognized and utilized in Asia. In Oceania areas, the degrees of utilization and
recognition of bibliometrics are much higher than those of scientometrics and informetrics.
Regarding African countries, the number of articles on the three areas is few and the level of
scientific research and production is low.
At the institutional level, universities account for the majority of the top 10 institutional
rankings of the three metrics. A total of 6, 7, and 4 European institutions enter the top 10
institutional rankings of bibliometrics, scientometrics, and informetrics. This finding shows
that European institutions play an important role in the three metrics.The main institutions of
Asia are mostly from China. With regard to American countries, only Indiana Univ enters the
top 10 institutional rankings of bibliometrics and scientometrics, and also ranks at the top in
informetrics. In African countries, South Africa’s Univ S Africa ranks fourth in informetrics.
This finding combined with the number of articles of South Africa shows that South Africa
presents strong research strength in informetrics.
At the author level, the top 10 high-yield authors in bibliometrics mainly include Bornmann,
Abramo, and Ho; those in scientometrics mainly include Groneberg, Ho, and Leydesdorff;
those in informetrics mainly include Egghe, Rousseau, and Burrell. Egghe and Rousseau enter
only the top 10 author rankings in informetrics.
Cooperation network
Author cooperation network
Figure 2 shows that seven large groups are present in the author cooperation network of
bibliometrics in 2007–2016. Notably, the size of the nodes represents the number of
publications of authors. D’Angelo, Abrano, Bornmann, and Ho, and other high-yield authors,
have their own fixed partners and present close cooperation within the group. Some authors
publish few articles but present many partnerships. For example, Waltman is in Ho’s
collaboration group and has a small number of articles but has six cooperative partners in the
threshold range. Moreover, Kostoff publishes few articles but collaborates with every member
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of the group. The said authors are inclined to conduct scientific research through cooperation.
In general, many cooperative groups exist in bibliometrics. The internal cooperative
relationship is close, collaborations between only two authors are few, and the degree of
cooperation is high.
Figure 2 Author cooperation network of bibliometrics
Figure 3 shows that scientometrics presents a large cooperation group and that Groneberg is
the center of the group. Leydesdorff and Bornmann are included in this group; however, the
two authors locate in the extension of the group. This group exhibits an intricate connection
and a close relationship. A prominent cooperative group exists, in which Ho of four fixed
partners is the center. Therefore, this group has a stable partnership. Many two- and three-
author groups exist. In general, the scale of the author collaboration network of scientometrics
is sparse.
Figure 3 Author cooperation network of scientometrics
Figure 4 shows that informetrics has a main cooperative group, in which Egghe and Rousseau
are the core, and includes Ye and Liu, among others. Egghe and Rousseau publish the largest
number of articles on informetrics. The rest of the groups is dispersed. Apart from the largest
group, more than 10 three- and two-author groups exist. The scale of the author cooperation
network is small.
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Figure 4 Author cooperation network of informetrics
The size of author cooperation depends on two main factors: the total number of articles and
the habit of research. With regard to the first factor, authors with large numbers of articles
have high numbers of cooperative relationships, thereby leading to large-scale cooperation.
For the second factor, some authors prefer to cooperate with other authors, thereby forming
large-scale and stable cooperation. Under the same thresholds, the number of large-scale
cooperative groups (more than five authors) in bibliometrics is more than that in
scientometrics and informetrics; however, the group relationships of the three metrics are tight.
Bibliometrics obtains the maximum number of literature and degrees of utilization and
recognition. The cooperative group with Groneberg as its core in scientometrics is the largest
among the three fields. The cooperative relationships among members are also frequent in the
three metrics. The decentralization degree of the author collaboration network of informetrics
is the sparsest among the three fields. Although its size of cooperative groups is the smallest,
informetrics possesses a major group with Egghe and Rousseau as its core.
Institutional cooperation network
In bibliometrics, the connection among institutions is tight and cooperation between
institutions is close. Europe is home to many research institutions, which attach great
importance to cooperation in bibliometrics. Only the Chinese Acad Sci has a purple aperture
in the cooperative network. Therefore, this institution presents high centrality and is an
important mediator in the entire cooperative group to date. Leiden Univ, Univ Granada, Asia
Univ, and CSIC exhibit many cooperative relations and publish several articles on
bibliometrics. Some institutions are very successful in cooperation even if they do not publish
many articles, such as Univ Amsterdam and Univ Carlos III Madrid.
The institutional collaboration network of scientometrics shows three large cooperative
groups (more than five institutions). In the first group, Asia Univ and Univ Amsterdam and
other high-yield organizations are the core. This group presents the largest number of
cooperative institutions among other groups, but its internal cooperation is sparse. In the
second group, Goethe Univ Frankfurt is the core. In the third and final group, Univ Granada
and CSIC are the core. In general, scientometrics presents a large number of cooperative
groups but in a small scale.
During the study period, informetrics possesses a significantly large cooperative group with
Katholieke Univ Leuven and Univ Antwerp as the core. This group also includes Univ
Hasselt and KHBO Assoc KU Leuven and other institutions. Notably, European institutions
account for the majority of the group. Some Chinese institutions are also present in this group,
such as Zhejiang Univ, Chinese Acad Sci, and Nanjing Univ. Therefore, Chinese and
European institutions exhibit frequent cooperation in informetrics. Indiana Univ (American)
and Dalian Univ Technol (Chinese) assume the role of intermediaries in their respective
groups. Although they are excluded in the main cooperative group, their degree of
cooperation is high.
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In general, under the same parameter setting, the degree of cooperation among the institutions
of bibliometrics is the highest, and the cooperative relationship of bibliometrics is close and
of the largest scale among the three metrics. Meanwhile, the cooperative relationship of
scientometrics and informetrics is dispersed. Only one to three large groups exist in
scientometrics and informetrics; thus, the scale of other groups is very small. However, the
scale of institutional cooperation is also affected by the total amount of literature and the habit
of specific authors (Yang et al., 2017).
Subject structure
We choose the co-words analysis to explore the subject structure of the three fields.
Considering the color confusion after clustering, we provide a screenshot of categories
depending on the color of each node prior to labeling the category name. The latter analysis is
based on the cluster name provided by Citespace. The clustering results are shown in Figs. 5,
6, and 7.
Figure 5 shows five main subjects in bibliometrics: 1) research on the general development
trend and influence of bibliometric analysis; 2) research based on bibliometric indicators of
the scientific research output, the ranking of universities, and the evaluation on individual
academic; 3) application of bibliometrics in scientific research management; 4) research on
cooperation network and model, application of text mining, and other new technologies in
other disciplines; 5) the use of the H index and other indicators to analyze the citation of
papers or other publications from various databases and thus evaluate the academic capability
and scientific research achievements.
Figure 5 Subject structure of bibliometrics
Figure 6 shows five main subjects in scientometrics; 1) application of scientometrics methods
in biology, indicating the extensive application of scientometrics methods in other fields; 2)
research on the quality of scientific research output and the research trend of scientometrics as
a branch of science; 3) research on scientometrics methods (such as citation analysis and
impact factors) based on journals and other research outputs, indicators (such as the H index),
and their application; 4) development trend of scientific cooperation, cooperation model, and
academic cooperation network based on scientific research output; 5) ranking or visualization
of discipline contents, personnel, and journals through scientometrics methods, as well as
research on the development trend of disciplines.
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Figure 6 Subject structure of scientometrics
Figure 7 shows five main subjects in informetrics; 1) research and application of the H index
and other new metrics in network environment, as well as research on information systems; 2)
research on the influence of articles and authors on the basis of informetrics methods and
citation analysis; 3) research on the distribution and ranking of high-impact articles, authors,
and journals based on the H index, as well as research on the model of informetrics; 4)
research on the development of informetrics and its relationship with bibliometrics and
scientometrics; 5) effect of network environment on the patterns of scientific research
activities.
Figure 7 Subject structure of informetrics
According to the keyword frequency, “science,” “citation,” “impact,” “Journal,” “citation
analysis,” “H index,” and “impact factor” rank among the top 10 keywords in the three areas.
Therefore, the three fields are concerned on the research and evaluation of the influence of
scientific research output. Most studies use the citation analysis method and pay attention to
the innovation and application of indexes.
In summary, the three metrics focus on evaluating scientific research output and investigating
the innovation and application of indexes (such as the H index) and the cooperation mode and
network. Bibliometrics focuses on exploring the development trend and research on the
application of bibliometrics in scientific research management. Scientometrics focuses on
exploring the application of its methods and techniques in other areas, the development of
citation analysis and other methods, and the quality of scientific research output and
development trends. Given that information is highly dependent on computer technology and
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mathematics, informetrics focuses on examining information system and the combination of
mathematical models and methods.
Citation situation
—
Mainly based on document co-citation network
According to the document co-citation network,the knowledge structure of bibliometrics
includes five components. Scientometrics is composed of six knowledge bases. Given that
three of these bases have the same theme (but different direction), we merge the three
identical parts into one. Finally, four components are obtained. The knowledge base of
informetrics consists of five parts . The connection between nodes in the graph represents the
citation relationship between the documents; the node with the purple aperture represents its
high important, and the size of the node represents the cited frequency. We compare the three
metrics on the basis of the cited literature with high centrality and high cited frequency.
According to the specific literature list, Hirsch’s An index to quantify an individual’s scientific
research output and Egghe’s Theory and practice of the G index are important documents in
the three fields. The two articles have been used as the bases for the study on the H index in
bibliometrics and scientometrics. Meanwhile, Hirsch’s article has also been used as the basis
for the study on evaluation and ranking in informetrics. Therefore, the same literature is used
in different angles in dissimilar fields. Hirsch (2005) proposed the H index to evaluate the
academic influence and the research level of researchers; this document is the first of the
branch. Egghe (2006) proposed the G index in 2006 to overcome the shortage of the H index,
and used the former index to measure the overall citation performance of a group of articles.
The H index is the common knowledge base of the three areas, which indicate that the three
metrics have attached importance to research on the innovation and application of evaluation
indicators.
As shown in Figure 7 and Table 1, #0 research trend, #3 scopus, and #4 gender disparity are
peculiar knowledge components of bibliometrics. #0 research trend involves the review on the
history of each specific research direction and the future prediction under the premise of
innovation of indicators and progress of research methods. Alonso et al. (2009) studied the H
index and the subsequent derivative index, and measured the application of the H index in
different fields. Bornmann and Daniel (2008) conducted a review of scientists’ citation
behavior and analyzed the motivations, impact factors, and trends of the citation. #3 scopus
presents diverse data sources in the context of the development of network; in this part,
researchers focus on emerging data search tools and their data coverage, search capabilities,
and the impact of scientific research (Meho & Yang, 2007; Falagas et al., 2008). #4 gender
disparity is the part wherein researchers in medicine evaluate the academic productivity and
influence of researchers using the H index to study whether the gender differences can lead to
differences in academic productivity (Eloy et al., 2012).
Figure 7 Literature citation figure of bibliometrics
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Table 1 Important basic literature of bibliometrics
As shown in the document co-citation network and the specific literature list of scientometrics,
#1–4 scientometric approach and #5 scientometric are peculiar knowledge components of
scientometrics. #1–4 scientometric approach is the basis of two research directions. King
measured (2004) the status and influence of national scientific research with scientometrics
methods, and Moed (2005) explored the application of citation analysis in scientific
evaluation. The two documents provided an empirical basis for the application of
scientometrics methods in the scientific evaluation. Konur applied scientometrics methods to
the quantitative research in biochemistry, and this document provided the knowledge base for
the application of scientometrics methods to different fields. #5 scientometric mainly contains
the scientific basis of visualization technology and social network analysis in scientometrics.
Chen (2006, 2010) developed CiteSpace, which is an important visualization tool for studies
on subject topics and trends, and its functions are constantly optimized and improved to date.
As shown in the document co-citation network and the specific literature list of informetrics,
#0 ranking, #2 pagerank, and #4 Lotkas law are peculiar knowledge components of
informetrics. #0 ranking is mainly based on the articles of Hirsch (2005) and Braun et al.
(2006), who studied the assessment and ranking of academic impact on individuals and
journals using the H index, thereby establishing the foundation for the innovation and
application of indicators in ranking and evaluation of scientific research. #2 pagerank is the
part wherein Ding (2009) studied factors that affect the ranking of the PageRank algorithm,
and proposed the weighted PageRank algorithm. The study provided experience for the
further application of the PageRank algorithm in informetrics. #4 Lotkas law is the part
wherein the basic knowledge theory is comprehensively explored and the mathematical model
is applied to the theoretical hypothesis.
Discussion and Conclusion
We retrieve the literature (such as articles, reviews, and proceeding papers) on the three
metrics from SCI-Expanded, SSCI, and A&HCI using the three terms between 2007 and 2016.
The results show that the three metrics differ in the degrees of utilization and recognition but
are similar in the general direction.
1) Recognition. Combining the number of articles in national and institution levels shows that
Europe is the core area of the three fields. The degrees of recognition of bibliometrics and
scientometrics are high in America. The degree of recognition of scientometrics is higher than
that of the two other fields in Asia, and the degree of recognition of bibliometrics is much
higher than that of the two other fields in Oceania. The degrees of recognition of the three
fields are low in Africa, but the degree of recognition of informetrics is high in South Africa.
Bibliometrics is the most frequently used and has the largest degree of increase among the
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three terms, so we think that the term "bibliometrics" can be used as a general term for
“scientometrics” and “informetrics” in order to avoid confusion in terms.
2) Cooperation. Universities are the main institutions in the three metrics. The scale of the
cooperative group of bibliometrics is larger than that of scientometrics and informetrics, and
the group relationships of bibliometrics are tight. Many two-author cooperative groups with
scattered scale exist in scientometrics. The author cooperative network of informetrics is the
sparsest and has the smallest scale among the three metrics. Bibliometrics has the highest
degree of institutional cooperation and the largest scale of institutional cooperation network.
On the contrary, the cooperative relationships of scientometrics and informetrics are dispersed,
and the size of the group is small.
3) Subject structure. Bibliometrics attaches great importance to the development of the three
metrics and the application of bibliometric methods in scientific research management. Other
disciplines use scientometrics when applying metrological methods, such as citation analysis.
Scientometrics emphasizes the quality of scientific research output and focuses on research on
scientometrics development trends. In the network environment, researchers prefer to use
informetrics when researching information systems and the combination of mathematical
models and informetrics methods.
4) Knowledge base. A significant difference is found in the knowledge base of the three
metrics. The H index is the common knowledge base of the three fields in focusing on
innovating and improving indicators. The peculiar knowledge bases of bibliometrics include
review on the history of each specific research direction, data coverage and search capabilities
of emerging data search tools, and application of bibliometrics in the medical field. The
peculiar knowledge bases of scientometrics include the application of scientometrics methods
in scientific evaluation and other disciplines, such as visualization techniques and social
network analysis. The peculiar knowledge bases of informetrics include comprehensive
exploration of the basic theory of and research on the PageRank algorithm.
This study presents a few limitations. The overall situation of the three metrics can be
accurately compared using long data period. However, this study uses only the data from
2007 to 2016. Although we carefully refine some terms and construct a document retrieval
formula, the data collection is still incomplete and thus cannot fully represent the data for the
three metrics. The current situation and relationships of the three metrics include various
aspects, but this study focuses on only three major areas. Therefore, the comparative analysis
is insufficient. Future research can conduct interview with experts, extend the data period,
perform in-depth content analysis, and use other methods in comparing the relationships
among the three metrics.
Acknowledgments
This research is funded by the National Social Science Fund Key Project of PR China (17ATQ009).
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... It serves scientific decision making and management using information that is generally from scientific publications [1][2][3][4][5]. The terminology "scientometrics" ("naukometriya") was coined in 1969 [6] and obtained broad acceptance; it has grown in popularity as the journal Scientometrics was established in 1978 [5,7]. Scientometrics is commonly synonymously referred to as informetrics, bibliometry, bibliometrics, bibliometric analysis, science mapping, or knowledge structure in the literature, although these terms are essentially recognized as separate fields [7]. ...
... The terminology "scientometrics" ("naukometriya") was coined in 1969 [6] and obtained broad acceptance; it has grown in popularity as the journal Scientometrics was established in 1978 [5,7]. Scientometrics is commonly synonymously referred to as informetrics, bibliometry, bibliometrics, bibliometric analysis, science mapping, or knowledge structure in the literature, although these terms are essentially recognized as separate fields [7]. Scientometrics originated in information and library science, but it has evolved over time and has been widely applied in a variety of other disciplines in order to identify research landscapes (e.g., growth, structure, interrelationship, and productivity) or map historical footprints, emerging hotspots, or scholarly fields [8,9]. ...
Scientometrics of Scientometrics Based on Web of Science Core Collection Data between 1992 and 2020
Article
Full-text available
  • Nov 2023
Scientometrics is a quantitative and statistical approach that analyzes research on certain themes. It originated from information/library science but has been applied in various disciplines, including information science, library science, natural science, technology, engineering, medical sciences, and social sciences and humanities. Numerous scientometric studies have been carried out, but no study has attempted to investigate the overall research status of scientometrics. The objective of this study was to investigate the research status of scientometrics based on 16,225 publications archived in the Web of Science Core Collection between 1992 and 2020. The results show that there has been a marked increase in publications on scientometric studies over the past decades, with “Information Science Library Science” being the predominant discipline publishing scientometric studies, but scientometrics has been widely adopted in a variety of other disciplines (240 of 254 Web of Science categories). It was found that Web of Science, Vosviewer, and Scientometrics are the most utilized database, software, and journal for scientometric studies, respectively. The most productive author (Lutz Bornmann from the Max Planck Society, Germany), organization (University of Granada, Spain), and country (USA) are also identified. In addition, high-impact scientometric studies and the research landscape are analyzed through citation networks and the co-occurrence of keywords method.
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... Scientometrics is a discipline that quantitatively analyzes researchers and research results with mathematical methods, reveals the scientific development process, quantifies scientific research activities with citation analysis and other methods, and provides a basis for scientific decision making and management [42][43][44]. The map of scientific knowledge is a bibliometric method [45]. ...
Science Mapping of Meta-Analysis in Agricultural Science
Article
Full-text available
  • Nov 2023
As a powerful statistical method, meta-analysis has been applied increasingly in agricultural science with remarkable progress. However, meta-analysis research reports in the agricultural discipline still need to be systematically combed. Scientometrics is often used to quantitatively analyze research on certain themes. In this study, the literature from a 30-year period (1992–2021) was retrieved based on the Web of Science database, and a quantitative analysis was performed using the VOSviewer and CiteSpace visual analysis software packages. The objective of this study was to investigate the current application of meta-analysis in agricultural sciences, the latest research hotspots, and trends, and to identify influential authors, research institutions, countries, articles, and journal sources. Over the past 30 years, the volume of the meta-analysis literature in agriculture has increased rapidly. We identified the top three authors (Sauvant D, Kebreab E, and Huhtanen P), the top three contributing organizations (Chinese Academy of Sciences, National Institute for Agricultural Research, and Northwest A&F University), and top three productive countries (the USA, China, and France). Keyword cluster analysis shows that the meta-analysis research in agricultural sciences falls into four categories: climate change, crop yield, soil, and animal husbandry. Jeffrey (2011) is the most influential and cited research paper, with the highest utilization rate for the Journal of Dairy Science. This paper objectively evaluates the development of meta-analysis in the agricultural sciences using bibliometrics analysis, grasps the development frontier of agricultural research, and provides insights into the future of related research in the agricultural sciences.
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... In this respect, incorporating the science mapping method helps to eliminate subjective interpretations, since it provides more insights into the investigated literature before conducting the systematic review [21]. Generally, to investigate the dynamics of literary production in a specific domain, science mapping studies make use of three distinct but overlapping methods: bibliometric analysis, scientometric analysis, and informetrics [22,23]. Compared to bibliometric analysis, which focuses primarily on reviewing the general properties of the relevant literature using mathematical and statistical methods, scientometric analysis extends beyond this to measure and analyze the literature to gain insights as to the practices of researchers and their socio-organizational structures. ...
Operations planning and scheduling in off-site construction supply chain management: Scope definition and future directions
Article
  • Jun 2023
  • AUTOMAT CONSTR
Efficient planning and scheduling of operations within the offsite construction supply chain is critical for the successful completion of projects. Despite significant efforts and the application of various approaches to improve planning and scheduling practices, the existing literature in this field lacks coherence and a comprehensive review that establishes the scope, boundaries, and categorization of planning and scheduling in supply chain operations remains unexplored. To address this research gap, this paper presents a structured framework for supply chain management that encompasses strategic planning, master planning and scheduling, and detailed planning and scheduling. Through an analysis of the literature, this paper identifies areas that have received insufficient attention from the research community, specifically strategic planning, the procurement stage, and logistics operations. To advance the field, future research should focus on the development of integrated planning and scheduling models that simultaneously consider multiple operations and incorporate realistic features of transportation and onsite tasks.
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Comparison of disciplines, topics, and methods in studies in Journal of Informetrics and Scientometrics from 2016 to 2020
Article
  • Feb 2024
This study compared topics, impact, disciplines, and research methods in articles published from 2016 to 2020 between Scientometrics and Journal of Informetrics (JOI) to provide referential data for researchers and understand developments in scientometric research. Regarding similarities between Scientometrics and JOI, the results revealed that authors affiliated with management-related institutes accounted for the largest group of researchers and were predominantly listed as the first authors. Methodology was the second most common topic, and the proportion of studies increased during the study period. Most researchers preferred combining various methods to analyze publications from different sources. Regarding the main differences between the two journals, articles on research-based communication and metrics and indicators dominated Scientometrics and JOI, respectively. Authors working for scientometric institutes were the second largest group of authors in JOI, whereas computer science authors were the second largest group in Scientometrics. The average impact of articles for each topic in JOI was higher than that of articles in Scientometrics.
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Kavramsal Olarak Bibliyometri, Bilimetri, Bilimsel Performans Analizi - Bilimsel Haritalama ve Bibliyometrik Veri Tabanları
Chapter
Full-text available
  • Dec 2023
Bibliyometri, diğer uygulamaların yanı sıra bilim insanlarının çıktılarını, üniversiteler arasındaki işbirliğini, devlete ait bilim fonlarının ulusal araştırma ve geliştirme performansı ve eğitim verimliliği üzerindeki etkisini değerlendirmek ve analiz etmek için önemli bir araçtır (Moral-Muñoz vd., 2020). Bibliyometrik parametrelerin anlamının doğru bir şekilde anlaşılması, araştırmacıların performans analizinde ve dergilerin atıf durumlarının analiz edilmesine yardımcı olur, alanda araştırmacıların doğru eser ve dergilere odaklanmasını sağlar ve akademik üretkenliğin nesnel ölçütler ile hesaplanmasını sağlamaktadır (Choudhri vd., 2015). Bir araştırma alanını incelemek için iki temel bibliyometrik yöntem belirlenmiştir. Bunlar; bilim haritalama ve performans analizidir. Performans analizi, bilimsel aktör gruplarını (ülkeler, üniversiteler, bölümler, araştırmacılar) belirleyerek ve bu grupların çalışmalarının etkisini bibliyografik verilere dayalı olarak değerlendirmeyi hedefler. Öte yandan, bir araştırma alanının entelektüel, sosyal veya kavramsal yapısından bilginin çıkarılması, bibliyografik ağlara dayalı bilim haritalama analizi yoluyla yapılabilir (Gutiérrez-Salcedo vd., 2018). Genellikle, bibliyometrik araştırmaların başlangıcından bugüne kadar, bilim haritalama olarak adlandırılan bibliyometrik ağların görselleştirilmesi fikri büyük ilgi görmüştür. Görselleştirme, yayınlar veya dergiler arasındaki atıf ilişkileri ağlarından araştırmacılar arasındaki ortak yazarlık ilişkileri ağlarına veya anahtar kelimeler arasındaki ortak oluşum ilişkileri ağlarına kadar birçok farklı bibliyometrik ağı analiz etmek için güçlü bir yaklaşım olarak öne çıkmıştır. Araştırmacılar zaman içinde giderek daha büyük ağları analiz etmeye başlamış, bu durum daha gelişmiş görselleştirme tekniklerine ve araçlarına ihtiyaç duyulmasına yol açmıştır (Van Eck & Waltman, 2014). Bibliyometrik ağları görselleştirmek ve bilimsel üretkenliği izlemek için kullanılabilecek birçok yazılım aracı vardır (Damar & Özdağoğlu, 2022; Damar vd., 2021; Damar & Aydın, 2021). Bu araçlardan bazıları genel istatistiksel veya ağ analizi araçlarıdır. Diğer araçlar ise bibliyometrik ağları görselleştirmek için özel olarak geliştirilmiştir. Bu çalışma içinde bibliometrik ve bilimetrik analizler için kullanılan popüler uygulamalar, web siteleri, raporlama araçları ve paket programlar açıklanmaktadır. Analizler için kullanılan popüler veri toplama kaynakları, performans analizi ve görselleştirme araçları da dahil olmak üzere bibliyometrik ve scientometrik analizler yapmak için mevcut çeşitli araçların güncel bir incelemesi ortaya konulmaktadır. Çalışmanın bilimsel üretkenlik izleme yaklaşımına ve yükseköğretim çalışmaları alanı adına bir farkındalık oluşturacağı ve kural koyucular ve alan araştırmacıları için oldukça faydalı bir eser olduğu düşünülmektedir. Bu amaçla aşağıda sırasıyla bilimsel üretkenlik çerçevesinde biliyometri ve bilimetri kavramları, bibliyometride kullanılan iki temel yöntem olan performans ve ağ analizleri, bibliyometrik veri tabanları okuyucunun ilgisine sunulmaktadır. ---------- Bibliometrics is an important tool for assessing and analyzing the output of scientists, collaboration between universities, the impact of government science funding on national research and development performance and educational productivity, among other applications (Moral-Muñoz et al., 2020). A proper understanding of the meaning of bibliometric parameters helps to analyze the performance of researchers and the citation status of journals, enables researchers in the field to focus on the right works and journals, and enables academic productivity to be calculated with objective criteria (Choudhri et al., 2015). Two basic bibliometric methods have been identified to examine a research field. These are science mapping and performance analysis. Performance analysis aims to identify groups of scientific actors (countries, universities, departments, researchers) and evaluate the impact of their work based on bibliographic data. On the other hand, the extraction of knowledge from the intellectual, social or conceptual structure of a research field can be done through science mapping analysis based on bibliographic networks (Gutiérrez-Salcedo et al., 2018). Generally, from the beginning of bibliometric research until today, the idea of visualizing bibliometric networks, called science mapping, has attracted great interest. Visualization has emerged as a powerful approach to analyze many different bibliometric networks, ranging from networks of citation relationships between publications or journals to networks of co-authorship relationships between researchers or networks of co-occurrence relationships between keywords. Over time, researchers have started to analyze larger and larger networks, leading to the need for more advanced visualization techniques and tools (Van Eck & Waltman, 2014). There are many software tools that can be used to visualize bibliometric networks and monitor scientific productivity (Damar & Özdağoğlu, 2022; Damar et al., 2021; Damar & Aydın, 2021). Some of these tools are general statistical or network analysis tools. Other tools are specifically developed to visualize bibliometric networks. This study describes popular applications, websites, reporting tools, and software packages used for bibliometric and scientometric analyses. It provides an up-to-date review of the various tools available for conducting bibliometric and scientometric analyses, including popular data collection sources used for analyses, performance analysis and visualization tools. It is believed that the study will raise awareness of the scientific productivity monitoring approach and the field of higher education studies and will be a very useful work for policy makers and researchers in the field. For this purpose, the concepts of sciometrics and sciometrics within the framework of scientific productivity, performance and network analysis, which are the two basic methods used in bibliometrics, and bibliometric databases are presented to the reader's interest respectively.
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Introduction to a Scientometrics Research Perspective in Applied Linguistics
Chapter
  • Feb 2024
Applied linguistics is a field that is becoming increasingly complex due to language constructs and its close relationship with neighboring disciplines like psycholinguistics. As an interdisciplinary field, applied linguistics consistently incorporates concepts from other areas, and researchers frequently redefine it to keep up with multilingual contexts, big data, technological advancements, and the impacts of globalization. To advance the field theoretically, researchers must address the complexities by problematizing and theorizing research methods. Scientometrics is one approach to doing so. In this chapter, we aim to provide readers with an overview of the volume – Scientometrics Research Perspective in Applied Linguistics. Our goal is to introduce the concept of scientometrics, differentiate it from related terms like bibliometrics, outline the various techniques used for data collection and analysis, highlight its applications in applied linguistics, provide reasons for editing the volume, and clarify the objectives of the volume. Moreover, we give a concise description of the chapters of this volume.
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Desiccation and crack behavior of modified waste materials–clay mixture as landfill liner: a systematic review
Article
  • Jan 2024
Cracking behavior can reduce soil hydraulic and mechanical properties and is a preferential pathway for water flow and pollutant transportation, resulting in polluted environment, such as application to landfill liners and capping. Recently, researchers have advocated the use of waste materials for clay mixtures using various measurement and analysis methods. Therefore, this study aims to conduct a bibliometric analysis of the scientific literature published between 2002 and 2021 obtained from Scopus to quantitatively identify research trends, key research areas, and future research paths in this field on desiccation and crack behavior using waste materials as landfill liners. The VOS viewer software was used to analyze 41 articles in which the paper selection process was filtered. The results showed that the fly ash mixture's application as a landfill liner could reduce cracking significantly. Furthermore, fractal analysis and X-ray computed tomography measurements have proven to be good candidates for measuring cracks because they are the most accurate for calculating the crack value. Waste materials such as fly ash can be applied as landfill liners with other materials, such as bentonite and coconut coir fibers. This study is beneficial for improving the design and selecting the appropriate materials for landfill liners.
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Kavramsal Olarak Bibliyometri, Bilimetri, Bilimsel Performans Analizi - Bilimsel Haritalama ve Bibliyometrik Veri Tabanları
Chapter
Full-text available
  • Jan 2024
Bibliyometri, diğer uygulamaların yanı sıra bilim insanlarının çıktılarını, üniversiteler arasındaki işbirliğini, devlete ait bilim fonlarının ulusal araştırma ve geliştirme performansı ve eğitim verimliliği üzerindeki etkisini değerlendirmek ve analiz etmek için önemli bir araçtır (Moral-Muñoz vd., 2020). Bibliyometrik parametrelerin anlamının doğru bir şekilde anlaşılması, araştırmacıların performans analizinde ve dergilerin atıf durumlarının analiz edilmesine yardımcı olur, alanda araştırmacıların doğru eser ve dergilere odaklanmasını sağlar ve akademik üretkenliğin nesnel ölçütler ile hesaplanmasını sağlamaktadır (Choudhri vd., 2015). Bir araştırma alanını incelemek için iki temel bibliyometrik yöntem belirlenmiştir. Bunlar; bilim haritalama ve performans analizidir. Performans analizi, bilimsel aktör gruplarını (ülkeler, üniversiteler, bölümler, araştırmacılar) belirleyerek ve bu grupların çalışmalarının etkisini bibliyografik verilere dayalı olarak değerlendirmeyi hedefler. Öte yandan, bir araştırma alanının entelektüel, sosyal veya kavramsal yapısından bilginin çıkarılması, bibliyografik ağlara dayalı bilim haritalama analizi yoluyla yapılabilir (Gutiérrez-Salcedo vd., 2018). Genellikle, bibliyometrik araştırmaların başlangıcından bugüne kadar, bilim haritalama olarak adlandırılan bibliyometrik ağların görselleştirilmesi fikri büyük ilgi görmüştür. Görselleştirme, yayınlar veya dergiler arasındaki atıf ilişkileri ağlarından araştırmacılar arasındaki ortak yazarlık ilişkileri ağlarına veya anahtar kelimeler arasındaki ortak oluşum ilişkileri ağlarına kadar birçok farklı bibliyometrik ağı analiz etmek için güçlü bir yaklaşım olarak öne çıkmıştır. Araştırmacılar zaman içinde giderek daha büyük ağları analiz etmeye başlamış, bu durum daha gelişmiş görselleştirme tekniklerine ve araçlarına ihtiyaç duyulmasına yol açmıştır (Van Eck & Waltman, 2014). Bibliyometrik ağları görselleştirmek ve bilimsel üretkenliği izlemek için kullanılabilecek birçok yazılım aracı vardır (Damar & Özdağoğlu, 2022; Damar vd., 2021; Damar & Aydın, 2021). Bu araçlardan bazıları genel istatistiksel veya ağ analizi araçlarıdır. Diğer araçlar ise bibliyometrik ağları görselleştirmek için özel olarak geliştirilmiştir. Bu çalışma içinde bibliometrik ve bilimetrik analizler için kullanılan popüler uygulamalar, web siteleri, raporlama araçları ve paket programlar açıklanmaktadır. Analizler için kullanılan popüler veri toplama kaynakları, performans analizi ve görselleştirme araçları da dahil olmak üzere bibliyometrik ve scientometrik analizler yapmak için mevcut çeşitli araçların güncel bir incelemesi ortaya konulmaktadır. Çalışmanın bilimsel üretkenlik izleme yaklaşımına ve yükseköğretim çalışmaları alanı adına bir farkındalık oluşturacağı ve kural koyucular ve alan araştırmacıları için oldukça faydalı bir eser olduğu düşünülmektedir. Bu amaçla aşağıda sırasıyla bilimsel üretkenlik çerçevesinde biliyometri ve bilimetri kavramları, bibliyometride kullanılan iki temel yöntem olan performans ve ağ analizleri, bibliyometrik veri tabanları okuyucunun ilgisine sunulmaktadır. ---------- Bibliometrics is an important tool for assessing and analyzing the output of scientists, collaboration between universities, the impact of government science funding on national research and development performance and educational productivity, among other applications (Moral-Muñoz et al., 2020). A proper understanding of the meaning of bibliometric parameters helps to analyze the performance of researchers and the citation status of journals, enables researchers in the field to focus on the right works and journals, and enables academic productivity to be calculated with objective criteria (Choudhri et al., 2015). Two basic bibliometric methods have been identified to examine a research field. These are science mapping and performance analysis. Performance analysis aims to identify groups of scientific actors (countries, universities, departments, researchers) and evaluate the impact of their work based on bibliographic data. On the other hand, the extraction of knowledge from the intellectual, social or conceptual structure of a research field can be done through science mapping analysis based on bibliographic networks (Gutiérrez-Salcedo et al., 2018). Generally, from the beginning of bibliometric research until today, the idea of visualizing bibliometric networks, called science mapping, has attracted great interest. Visualization has emerged as a powerful approach to analyze many different bibliometric networks, ranging from networks of citation relationships between publications or journals to networks of co-authorship relationships between researchers or networks of co-occurrence relationships between keywords. Over time, researchers have started to analyze larger and larger networks, leading to the need for more advanced visualization techniques and tools (Van Eck & Waltman, 2014). There are many software tools that can be used to visualize bibliometric networks and monitor scientific productivity (Damar & Özdağoğlu, 2022; Damar et al., 2021; Damar & Aydın, 2021). Some of these tools are general statistical or network analysis tools. Other tools are specifically developed to visualize bibliometric networks. This study describes popular applications, websites, reporting tools, and software packages used for bibliometric and scientometric analyses. It provides an up-to-date review of the various tools available for conducting bibliometric and scientometric analyses, including popular data collection sources used for analyses, performance analysis and visualization tools. It is believed that the study will raise awareness of the scientific productivity monitoring approach and the field of higher education studies and will be a very useful work for policy makers and researchers in the field. For this purpose, the concepts of sciometrics and sciometrics within the framework of scientific productivity, performance and network analysis, which are the two basic methods used in bibliometrics, and bibliometric databases are presented to the reader's interest respectively.
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A scientometric review of the peer-reviewed research on high tunnels in the United States
Article
Full-text available
  • Nov 2023
This study assessed the extant literature related to the use of high tunnels (HTs) in agricultural systems in the United States since the 2009 launch of the Natural Resources Conservation Service (NRCS) High Tunnel Initiative. This NRCS program led to an increase in HT adoption nationwide. The literature searches were conducted using the Web of Science (WoS) database. The final sample was 133 peer-reviewed articles published between 2009 and February 2023. We used CiteSpace 6.2.R1 and Gephi 0.9.2 to conduct co-citation, co-author, co-institution, and clustering techniques. The findings showed that the peer-reviewed literature about HT use has increased since 2009, substantially rising between 2017 and 2021. Horticulture was the top subject category in the literature, and most articles were published in peer-reviewed journals of the American Society for Horticultural Science (i.e., HortTechnology and HortScience). The research field evolved from general HT practices, nutrient management, and plant pathology to focus on trials of specific crops and integrated pest management. The institutions with the most contributions to the HT literature were Kansas State University, the University of Florida, Michigan State University, Purdue University, and the University of Minnesota. The patterns of HT research revealed in this study offer a greater understanding of the current state of knowledge to inform the focus of future research.
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The relationship between the author byline and contribution lists: a comparison of three general medical journals
Article
Full-text available
  • Jan 2017
  • SCIENTOMETRICS
The author byline is an indispensable component of a scientific paper. Some journals have added contribution lists for each paper to provide detailed information of each author’s role. Many papers have explored, respectively, the byline and contribution lists. However, the relationship between the two remains unclear. We select three prominent general medical journals: Journal of the American Medical Association (JAMA), Annals of Internal Medicine (Annals), and PLOS Medicine (PLOS). We analyze the relationship between the author byline and contribution lists using four indexes. Four main findings emerged. First, the number, forms, and names of contribution lists significantly differed among the three journals, although they adopted the criteria of the International Committee of Medical Journal Editors. Second, a U-shaped relationship exists between the extent of contribution and author order: the participation levels in contribution lists were highest for first authors, followed by last and second authors, and then middle authors with the lowest levels. Third, regarding the consistency between author order in the contribution list and byline, every contribution category has a high consistency in JAMA and Annals, while PLOS shows a low consistency, in general. Fourth, the three journals have a similar distribution for the first authors in the contribution category; the first author in the byline contributes the highest proportion, followed by the middle and second authors, and then the last author with the lowest proportion. We also develop recommendations to modify academic and writing practice: implement structured cross-contribution lists, unify formats and standards of contribution lists, draft the author contribution criteria in the social sciences and humanities, and consider author contribution lists in scientific evaluation.
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Statistical Bibliography or Bibliometrics?
Article
Full-text available
  • Jan 1969
  • J DOC
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What do citation counts measure? A review of studies on citing behavior. J Doc 64(1):45-80 (DOI: 10.1108/00220410810844150)
Article
Full-text available
  • Jan 2008
  • J DOC
Purpose – The purpose of this paper is to present a narrative review of studies on the citing behavior of scientists, covering mainly research published in the last 15 years. Based on the results of these studies, the paper seeks to answer the question of the extent to which scientists are motivated to cite a publication not only to acknowledge intellectual and cognitive influences of scientific peers, but also for other, possibly non‐scientific, reasons. Design/methodology/approach – The review covers research published from the early 1960s up to mid‐2005 (approximately 30 studies on citing behavior‐reporting results in about 40 publications). Findings – The general tendency of the results of the empirical studies makes it clear that citing behavior is not motivated solely by the wish to acknowledge intellectual and cognitive influences of colleague scientists, since the individual studies reveal also other, in part non‐scientific, factors that play a part in the decision to cite. However, the results of the studies must also be deemed scarcely reliable: the studies vary widely in design, and their results can hardly be replicated. Many of the studies have methodological weaknesses. Furthermore, there is evidence that the different motivations of citers are “not so different or ‘randomly given’ to such an extent that the phenomenon of citation would lose its role as a reliable measure of impact”. Originality/value – Given the increasing importance of evaluative bibliometrics in the world of scholarship, the question “What do citation counts measure?” is a particularly relevant and topical issue.
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Informetrics: Theory, methods and applications
Book
  • Apr 2017
This book provides an accessible introduction to the history, theory and techniques of informetrics. Divided into 14 chapters, it develops the content system of informetrics from the theory, methods and applications; systematically analyzes the six basic laws and the theory basis of informetrics and presents quantitative analysis methods such as citation analysis and computer-aided analysis. It also discusses applications in information resource management, information and library science, science of science, scientific evaluation and the forecast field. Lastly, it describes a new development in informetrics- webometrics. Providing a comprehensive overview of the complex issues in today's environment, this book is a valuable resource for all researchers, students and practitioners in library and information science. © Springer Nature Singapore Pte Ltd. 2017. All rights reserved.
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Biblio-, sciento-, infor-metrics?? what are we talking about ?
Article
  • Jun 2005
This paper traces the origins of informatics, scientometrics and informetrics in the USSR and Hungary; the origins of information science, information studies and bibliometrics in Britain and the USA, and their interactions with library studies. Finaqly, three different contexts are suggested in which the three '-metrics' have distinctive and important rules.
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Empirical Hyperbolic Distributions (Bradford-Zipf-Mandelbrot) for Bibliometric Description and Prediction
Article
  • Dec 1969
  • J DOC
Purpose - Aims to build on the work of Buckland and Hindle regarding statistical distribution as applied to the field of bibliometrics, particularly the use of empirical laws. Design/methodology/approach - Gives examples of hyperbolic distributions that have a bearing on the bibliometric application, and discusses the characteristics of hyperbolic distributions and the Bradford distribution. Findings - Hyperbolic distributions are the inevitable result of combinatorial necessity and a tendency to short-term rational behaviour. Originality/value - Supports Bradford's conclusion from his law, i.e. that to know about one's speciality, one must go outside it.
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Editorial: Expansion of the field of informetrics: Origins and consequences
Article
  • Dec 2005
  • INFORM PROCESS MANAG
An abstract is not available.
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Measurement of Science. Study of the Development of Science as an Information Process
Article
  • Jan 1971
A detailed analysis of the nature of science as an information system is presented in this book translated from the Russian version by the Foreign Technology Division of the Wright-Patterson Air Force Base. An analysis is provided of the increase in numbers of publications, journals, and scientists. The effect of the information crisis on the development of informal networks of scientists who exchange pre-publication copies of research reports is outlined, and the effect of the growth of these "invisible collectives," which provide essentially private knowledge, on the progress of Russian science is discussed: in the past, Soviet scientists have contributed to, and depended upon, the public knowledge in the journals. The language of bibliographic citations, which can be used to establish conceptual relationships between publications, is discussed as an alternative to indexing via structured vocabularies. Difficulties with the evaluation of effectiveness of the invisible collectives in the absence of public bibliographic citation are outlined. The contribution of different countries to world science information flow is estimated. (AL)
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