# Loet Leydesdorff: bibliometric analysis and mapping of his scientific production

Audilio Gonzales-Aguilar, María-Jesús Colmenero-Ruiz, Francisco-Carlos

Paletta, Lise Verlaet

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Audilio Gonzales-Aguilar, María-Jesús Colmenero-Ruiz, Francisco-Carlos Paletta, Lise Verlaet. Loet Leydesdorff: bibliometric analysis and mapping of his scientific production. El profesional de la información, 2023, 32 (7), pp.e320709. 10.3145/epi.2023.dic.09 . hal-04608851

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# Loet Leydesdorff: bibliometric analysis and mapping of his scientific production

Audilio Gonzales-Aguilar; María-Jesús Colmenero-Ruiz; Francisco-Carlos Paletta; Lise Verlaet

**Nota:** Este artículo se puede leer en español en:
https://revista.profesionaldelainformacion.com/index.php/EPI/article/view/87543

**Recommended citation:**

Gonzales-Aguilar, Audilio; Colmenero-Ruiz, María-Jesús; Paletta, Francisco-Carlos; Verlaet, Lise (2023). "Loet Leydesdorff: bibliometric analysis and mapping of his scientific production". *Profesional de la información*, v. 32, n. 7, e320709.

https://doi.org/10.3145/epi.2023.dic.09

Article received on December 01st 2023
Approved on December 17th 2023

<figure><img src="image_2.png" /><figcaption>**Audilio Gonzales-Aguilar**</figcaption></figure>

<figure><img src="image_3.png" /></figure>

https://orcid.org/0000-0001-8693-2076

Université Paul-Valéry Montpellier III
Département de Documentation
Montpellier, France
audilio.gonzales@gmail.com

<figure><img src="image_4.png" /><figcaption>**María-Jesús Colmenero-Ruiz**</figcaption></figure>

https://orcid.org/0000-0002-1650-1091

Universidad Complutense de Madrid
Santísima Trinidad, 37
28010 Madrid, Spain
mcolmene@ucm.es

<figure><img src="image_5.png" /><figcaption>**Francisco-Carlos Paletta**</figcaption></figure>

https://orcid.org/0000-0002-4112-5198

Universidade de São Paulo
Departamento de Informação e Cultura
São Paulo, Brazil
fcpaletta@usp.br

<figure><img src="image_6.png" /><figcaption>**Lise Verlaet**</figcaption></figure>

https://orcid.org/0000-0002-3909-0184

Université Paul-Valéry Montpellier III
Département de Documentation
Montpellier, France
lise.verlaet@univ-montp3.fr

## Abstract

This study conducts a comprehensive bibliometric analysis and mapping of the scientific production of Loet Leydesdorff. Leveraging bibliometric techniques, the research aims to explore the breadth and impact of Leydesdorff's scholarly contributions. The analysis includes an examination of his publication patterns, citation impact, and collaborations over time. Additionally, mapping techniques will be employed to visually represent the networks and interdisciplinarity associated with Leydesdorff's work. The study provides insights into the evolution of his research interests, the influence of his contributions within the scientific community, and the interdisciplinary connections inherent in his body of work.

## Keywords

Bibliometric analysis; Bibliometrics; *Biblioshiny*; *Web of Science*; *Cosma*; Text analysis; Social network analysis; Mapping; Researchers; Loet Leydesdorff.

## Acknowledgements

We express our sincere thanks to Tomàs Baiget for his kind invitation to contribute an article in homage to Loet Leydesdorff.
"Citation analysis has conquered the world of science policy analysis"
(Amsterdamska; Leydesdorff, 1988)

**1. Introduction**

Loet Leydesdorff was a Dutch sociologist of science and science communication researcher. He received his PhD in So-
ciology of Science from the University of Amsterdam in 1979 with a thesis entitled "Dynamic and stochastic models for
reciprocal citation processes" (Leydesdorff, 1979). His research focused mainly on the application of complex systems
theory to scientific communication.

Died in March 2023, Leydesdorff is internationally recognised for his contributions to the mapping and analysis of scien-
tific collaboration networks. In (Leydesdorff, 2007a) he proposed the use of "intermediate centrality" as an indicator of
the interdisciplinarity of scientific journals. Furthermore, his innovative methods for visualising and analysing networks,
as shown in (Leydesdorff; Ràfols, 2009), offer a unique perspective on the global structure of scientific research.

Simultaneously, Leydesdorff developed sociological mo-
dels of scientific communication. His book "A sociologi-
cal theory of communication: The self-organization of
the knowledge-based society", explores the dynamics of
knowledge-based societies (Leydesdorff, 2001). He has

also contributed to understanding the dynamics of scientific research, as evidenced in (Leydesdorff; Meyer, 2010), on
the decline of university patents. Together with Henry Etzkowitz, he developed the Triple Helix model, a conceptual mo-
del that describes the interaction and collaboration between universities, industries and governments in the innovation
process (Etzkowitz; Leydesdorff, 1996), with great repercussions in the area. The breadth of Loet Leydesdorff's contri-
butions to the understanding of research networks, scientific communication, innovation and the sociology of science
is noteworthy.

Bibliometric analysis is a macroscopic tool for extracting and discovering knowledge from a large amount of research literature very quickly compared to a traditional systematic review. In recent years, bibliometric analysis has attracted the interest of researchers for various reasons, such as the emergence of digital technologies or bibliometric software like VOSviewer, CiteSpace and Biblioshiny and the development of academic databases like Web of Science, Scopus and Google Scholar (Moral-Muñoz et al., 2020).

Bibliometric analysis uses both quantitative and qualitative methods. Quantitative methods include descriptive and per-
formance metrics of the research output of a field (the number of publications or citations, etc.), as well as the identifica-
tion of the most important research constituents (the most cited articles, the most productive sources, etc.). Qualitative
methods include the analysis of scientific mapping to explore the relationships between research constituents (Donthu,
2021). Scientific mapping is carried out by analysing networks of textual units, with techniques such as co-word analysis,
co-citation analysis and collaboration analysis (Zupic; Čater, 2015).

This paper is structured as follows: section 2 presents the methodology used. Section 3 provides the results of the bibliometric analysis. Section 4 presents the interactive mapping analysis to explore the relationships between the elements studied (co-authors, keywords, keywords plus and publications). Finally, section 5 provides a brief summary of the main results and conclusions of the work.

**2. Methodology**

This section describes the research methodology used. The data were obtained from the Web of Science (WoS) Core
Collection database, with the search phrase "L. Leydesdorff OR Loet Leydesdorff":
http://www.webofscience.com

Figure 1 gives an overview of the data corpus.

Based on them, a bibliometric analysis was carried out to answer the research questions, which involves, on the one
hand, a statistical analysis and, on the other hand, the visualisation of the research production of a field. This bibliom-
metric analysis was carried out using Bibliometrix, an open source software, supported by the R environment, which
provides tools for the calculation of performance metrics (Aria; Cuccurullo, 2017):
https://www.bibliometrix.org/home

Bibliometrix is integrated with Biblioshiny, a web interfa-
ce for bibliometric network visualisation. The statistical
analysis consisted of a performance analysis to show pu-
blication and citation patterns, publications, authors and
countries, as well as the most cited articles. For visuali-
sation, publications were mapped to explore topic and
keyword trends through co-word analysis, co-citation
clusters through co-citation analysis, and collaboration

Together with Henry Etzkowitz, he de-
veloped the Triple Helix model, a concep-
tual model that describes the interaction
and collaboration between universities,
industries and governments in the inno-
vation process
structure between countries through collaboration analysis. The latter results were visualised in the form of networks. The workflow steps followed for the bibliometric analysis were: study design, data collection, data analysis, and visualisation and interpretation of the results (Zupić; Čater, 2015).

The main objective is to examine and visualise Loet Leydesdorff's scientific publications from 1980 to 2023. The research questions of this study are as follows:

- What is the evolution of publications and citations?

- What are the most relevant and influential sources, countries and publications?

- What are the most common research topics and keyword trends in Leydesdorff research?

- What are the main co-citation clusters?

- What is the collaborative network of countries in social media research?

In addition, a scientific network cartography has been created, made up of this set of publications belonging to this author, with the idea of displaying it interactively on the web and with the possibility of downloading it. The software used for this has been Cosma, a software for the visualisation of documentary graphs (Perret et al., 2021). In the section corresponding to the cartography we will explain in more detail its characteristics and functionalities.

The Table 1 presents a summary of the main information about the dataset. Specifically, our dataset contains 424 articles published between 1980 and 2023. These articles were published in 101 different scientific sources. The sources are made up of various types of documents: scientific journal articles, conference papers, books and book chapters, reviews, etc. The average number of years it takes for an article to be cited is approximately 0.92 and each article has on average 50.71 citations. The total number of references cited in all articles is 7486. In addition, the articles contain 3,297 author keywords and 1,470 plus (additional) keywords.

Author keywords are keywords defined by authors to determine the content of their publications, while keywords plus are keywords generated by the WoS database from titles, keywords and abstracts of publications. Our dataset covers a number of single-authored publications of 112, and the rest were co-authored with a total of 197 co-authors. On average, each article is written by about 3 authors (i.e. authors per paper is 3.48). The collaboration rate is around 2.27 for the total set.

Figure 1 visually summarises the data presented in table 1.

<table><caption>Table 1. Main information on the bibliographic dataset</caption><thead><tr><th>Description</th><th>Results</th></tr></thead><tbody><tr><td>Period</td><td>1980:2023</td></tr><tr><td>Sources (journals, books, etc.)</td><td>101</td></tr><tr><td>Documents</td><td>424</td></tr><tr><td>Annual growth rate</td><td>2,59</td></tr><tr><td>Average age of documents</td><td>13,5</td></tr><tr><td>Average number of citations per document</td><td>50,71</td></tr><tr><td>References</td><td>7486</td></tr><tr><td colspan="2"><strong>Content of the documents</strong></td></tr><tr><td>Plus Keywords (ID)</td><td>423</td></tr><tr><td>Author Keywords (DE)</td><td>592</td></tr><tr><td colspan="2"><strong>Authors</strong></td></tr><tr><td>Authors</td><td>197</td></tr><tr><td>Authors of single-authored documents</td><td>1</td></tr><tr><td colspan="2"><strong>Collaboration of authors</strong></td></tr><tr><td>Single-authored documents</td><td>112</td></tr><tr><td>Co-authors per paper</td><td>2,27</td></tr><tr><td>International co-authorships %</td><td>57,78</td></tr><tr><td colspan="2"><strong>Types of documents</strong></td></tr><tr><td>articles</td><td>314</td></tr><tr><td>articles; book chapters</td><td>9</td></tr><tr><td>article; conference proceedings</td><td>5</td></tr><tr><td>book review</td><td>6</td></tr><tr><td>proofreading</td><td>2</td></tr><tr><td>editorial material</td><td>23</td></tr><tr><td>letter</td><td>28</td></tr><tr><td>meeting summary</td><td>2</td></tr><tr><td>news</td><td>1</td></tr><tr><td>note</td><td>2</td></tr><tr><td>minutes</td><td>28</td></tr><tr><td>retraction</td><td>1</td></tr><tr><td>summary</td><td>3</td></tr></tbody></table>

<figure><img src="image_7.png" /><figcaption>Figure 1. Summary of the main information on the dataset</figcaption></figure>
## 3. Results

This section presents and interprets the results of the bibliometric analysis based on the research questions of our study.

### 3.1. Evolution of publications and citations, sources, countries and most relevant publications.

Presented in this subsection are the results that answer the question: What is the evolution of Loet Leydesdorff's publications and citations on the research topics of his publications (Table 2 and Figure 2).

<table><caption>Table 2. Distribution of publications and citations</caption><thead><tr><th>Year</th><th>Nº of publications</th><th>Total cites</th><th>Year</th><th>Nº of publications</th><th>Total cites</th><th>Year</th><th>Nº of publications</th><th>Total cites</th></tr></thead><tbody><tr><td>1980</td><td>1</td><td>2</td><td>1996</td><td>4</td><td>124</td><td>2010</td><td>21</td><td>1.513</td></tr><tr><td>1981</td><td>1</td><td>3</td><td>1997</td><td>5</td><td>182</td><td>2011</td><td>26</td><td>1.323</td></tr><tr><td>1982</td><td>1</td><td>2</td><td>1998</td><td>5</td><td>504</td><td>2012</td><td>28</td><td>1.498</td></tr><tr><td>1984</td><td>1</td><td>2</td><td>1999</td><td>2</td><td>38</td><td>2013</td><td>30</td><td>1.048</td></tr><tr><td>1986</td><td>1</td><td>65</td><td>2000</td><td>8</td><td>3.843</td><td>2014</td><td>27</td><td>1.233</td></tr><tr><td>1987</td><td>5</td><td>143</td><td>2001</td><td>5</td><td>43</td><td>2015</td><td>27</td><td>978</td></tr><tr><td>1988</td><td>2</td><td>1</td><td>2002</td><td>4</td><td>79</td><td>2016</td><td>22</td><td>548</td></tr><tr><td>1989</td><td>5</td><td>255</td><td>2003</td><td>7</td><td>293</td><td>2017</td><td>19</td><td>462</td></tr><tr><td>1990</td><td>4</td><td>115</td><td>2004</td><td>5</td><td>220</td><td>2018</td><td>12</td><td>201</td></tr><tr><td>1991</td><td>4</td><td>92</td><td>2005</td><td>11</td><td>1.097</td><td>2019</td><td>21</td><td>260</td></tr><tr><td>1992</td><td>5</td><td>40</td><td>2006</td><td>15</td><td>1.443</td><td>2020</td><td>11</td><td>65</td></tr><tr><td>1993</td><td>3</td><td>126</td><td>2007</td><td>15</td><td>691</td><td>2021</td><td>9</td><td>64</td></tr><tr><td>1994</td><td>7</td><td>155</td><td>2008</td><td>15</td><td>1.042</td><td>2022</td><td>4</td><td>40</td></tr><tr><td>1995</td><td>2</td><td>12</td><td>2009</td><td>21</td><td>1.463</td><td>2023</td><td>3</td><td>4</td></tr></tbody></table>

<figure><img src="image_8.png" /><figcaption>Figure 2. Annual scientific production</figcaption></figure>

Table 2 shows the distribution of publications and citations for the 43-year period between 1980 and 2023. The highest number of publications is between 2006 and 2019, representing 66% (280) of the total number of publications. In the years 2020 to 2023, there was a decrease in the number of publications compared to the previous years.

Below are presented the results to answer the question: What are Leydesdorff's most relevant sources, countries and publications? Table 3 and Figure 3 present the 10 scientific journals where he published the most. These journals cover 64.1% of the total number of publications in our dataset. The top three journals that cover articles in Leydesdorff's research areas are *Scientometrics*, *Journal of the American Society for Information Science and Technology* and *Journal of informetrics*.

<table><caption>Table 3. Top 10 scientific journals where Loet published more</caption><thead><tr><th>Sources</th><th>Articles</th></tr></thead><tbody><tr><td>Scientometrics</td><td>93</td></tr><tr><td>Journal of the American Society for Information Science and Technology</td><td>55</td></tr><tr><td>Journal of informetrics</td><td>45</td></tr><tr><td>Journal of the Association for Information Science and Technology</td><td>28</td></tr><tr><td>Research policy</td><td>15</td></tr><tr><td>Profesional de la información</td><td>10</td></tr><tr><td>Social science information sur les sciences sociales</td><td>8</td></tr><tr><td>Technological forecasting and social change</td><td>7</td></tr><tr><td>Systems research and behavioral science</td><td>6</td></tr><tr><td>17<sup>th</sup> International conference on scientometrics & informetrics (ISSI2019), vol. 1</td><td>5</td></tr></tbody></table>
<figure><img src="image_9.png" /><figcaption>Figure 3. Top 10 scientific journals where Loet published more</figcaption></figure>

Table 4 shows the top 10 most cited journals in the field. The most cited journals in the field measure the number of citations in the field received per cited reference within the reference lists of the publications in the dataset. From these results, we can see that *Scientometrics* is the most cited source among researchers. This source has been cited 1886 times. The second most cited source is *Journal of the American Society for Information Science and Technology* (1243 times), followed by *Research Policy* (887 times). This shows that these journals are the main references for publications by this author and his co-authors.

<table><caption>Table 4. The most cited journals in the field</caption><thead><tr><td>Sources</td><td>Articles</td></tr></thead><tbody><tr><td>Scientometrics</td><td>1886</td></tr><tr><td>Journal of the American Society for Information Science and Technology</td><td>1558</td></tr><tr><td>Research policy</td><td>887</td></tr><tr><td>Journal of informetrics</td><td>661</td></tr><tr><td>Science</td><td>236</td></tr><tr><td>Social networks</td><td>184</td></tr><tr><td>Journal of the Association for Information Science and Technology (Jasist)</td><td>173</td></tr><tr><td>Nature</td><td>160</td></tr><tr><td>Social studies of science</td><td>160</td></tr><tr><td>Social science information</td><td>141</td></tr></tbody></table>

<figure><img src="image_10.png" /><figcaption>Figure 4. The most cited journals in the field.</figcaption></figure>
Table 5 presents the top 10 most influential publications in terms of total citations. The total number of citations of a journal is the number of citations received by the articles published in that journal in the dataset. From these results it can be seen that the top three journals, *Journal of the American Society for Information Science and Technology*, *Scientometrics* and *Journal of informetrics*, have published many articles that have received a high number of total citations with a high h-index.

However, there are also magazines, such as *Journal of the Association for Information Science and Technology* and *Research Policy et Social Science*, which have a high number of citations with a limited number of articles published in Leydesdorff's publications.

<table><caption>Table 5. Top 10 most influential journals by total citations</caption><thead><tr><td>Journals</td><td>h index</td><td>g index</td><td>m_index</td><td>Total citations</td><td>Number of publications</td><td>Start year</td></tr></thead><tbody><tr><td>Journal of the American Society for Information Science and Technology</td><td>36</td><td>55</td><td>1,565</td><td>4388</td><td>55</td><td>2001</td></tr><tr><td>Scientometrics</td><td>34</td><td>56</td><td>0,791</td><td>3491</td><td>93</td><td>1981</td></tr><tr><td>Journal of informetrics</td><td>27</td><td>45</td><td>1,688</td><td>2.41</td><td>45</td><td>2008</td></tr><tr><td>Journal of the Association for Information Science and Technology</td><td>18</td><td>28</td><td>1,8</td><td>1102</td><td>28</td><td>2014</td></tr><tr><td>Research policy</td><td>14</td><td>15</td><td>0,35</td><td>5937</td><td>15</td><td>1984</td></tr><tr><td>Social science information sur les sciences sociales</td><td>7</td><td>8</td><td>0,219</td><td>101</td><td>8</td><td>1992</td></tr><tr><td>Technological forecasting and social change</td><td>7</td><td>7</td><td>0,368</td><td>254</td><td>7</td><td>2005</td></tr><tr><td>Profesional de la informacion</td><td>6</td><td>10</td><td>0,375</td><td>172</td><td>10</td><td>2008</td></tr><tr><td>Plos one</td><td>5</td><td>5</td><td>0,357</td><td>276</td><td>5</td><td>2010</td></tr><tr><td>Journal of data and information science</td><td>4</td><td>4</td><td>0,571</td><td>55</td><td>4</td><td>2017</td></tr></tbody></table>

Table 6 shows the data for the 20 countries where this author has published the most; SCP stands for *Single Country Publication* (refers to scientific publications originating from a single country. That is, all the main authors or affiliations are located in a single country); MCP is *Multiple Country Publication* (refers to scientific publications involving collaboration of authors or affiliations from several countries) *MCP ratio* (this is the measure that indicates the proportion of the total number of publications that are collaborative between authors or affiliations from different countries.

These results show that between the Netherlands and Germany, 299 articles have been published and 98 of them involved international collaborations. The third country with the highest number of publications is the United States, with 23 international collaborations.

However, some observations can be made about the proportion of CCMs. Countries such as Germany, China and the UK have a higher degree of international collaboration than other countries.

<table><caption>Table 6. The 20 most frequent countries of origin of authors and co-authors of publications</caption><thead><tr><td>Country</td><td>Articles</td><td>SCP</td><td>MCP</td><td>Freq</td><td>MCP_Ratio</td></tr></thead><tbody><tr><td>Netherlands</td><td>258</td><td>160</td><td>98</td><td>0,608</td><td>0,38</td></tr><tr><td>Germany</td><td>41</td><td>0</td><td>41</td><td>0,097</td><td>1,00</td></tr><tr><td>USA</td><td>25</td><td>2</td><td>23</td><td>0,059</td><td>0,92</td></tr><tr><td>China</td><td>22</td><td>0</td><td>22</td><td>0,052</td><td>1,00</td></tr><tr><td>United Kingdom</td><td>17</td><td>0</td><td>17</td><td>0,040</td><td>1,00</td></tr><tr><td>Russia</td><td>8</td><td>0</td><td>8</td><td>0,019</td><td>1,00</td></tr><tr><td>Korea</td><td>7</td><td>0</td><td>7</td><td>0,017</td><td>1,00</td></tr><tr><td>Switzerland</td><td>6</td><td>1</td><td>5</td><td>0,014</td><td>0,83</td></tr><tr><td>Belgium</td><td>4</td><td>0</td><td>4</td><td>0,009</td><td>1,00</td></tr><tr><td>Italy</td><td>3</td><td>0</td><td>3</td><td>0,007</td><td>1,00</td></tr><tr><td>Colombia</td><td>2</td><td>0</td><td>2</td><td>0,005</td><td>1,00</td></tr><tr><td>France</td><td>2</td><td>1</td><td>1</td><td>0,005</td><td>0,50</td></tr><tr><td>Hungary</td><td>2</td><td>0</td><td>2</td><td>0,005</td><td>1,00</td></tr><tr><td>India</td><td>2</td><td>0</td><td>2</td><td>0,005</td><td>1,00</td></tr><tr><td>Norway</td><td>2</td><td>0</td><td>2</td><td>0,005</td><td>1,00</td></tr><tr><td>Australia</td><td>1</td><td>0</td><td>1</td><td>0,002</td><td>1,00</td></tr><tr><td>Cuba</td><td>1</td><td>0</td><td>1</td><td>0,002</td><td>1,00</td></tr><tr><td>Finland</td><td>1</td><td>0</td><td>1</td><td>0,002</td><td>1,00</td></tr><tr><td>Ireland</td><td>1</td><td>0</td><td>1</td><td>0,002</td><td>1,00</td></tr></tbody></table>
<figure><img src="image_11.png" /><figcaption>Figure 5. Top 20 countries of origin of authors and co-authors of publications</figcaption></figure>

Finally, Table 7 presents the ranking of Leydesdorff's most cited articles.

<table><caption>Table 7. Ranking of most cited publications</caption><thead><tr><td>Lead author - Publication</td><td>Title</td><td>Total citations</td></tr></thead><tbody><tr><td>Etzkowitz H, 2000, Res policy</td><td>The dynamics of innovation: from National Systems and "Mode 2" to a Triple Helix of university-industry-government relations<br>10.1016/S0048-7333(99)00055-4</td><td>3,491</td></tr><tr><td>Wagner CS, 2005, Res policy</td><td>Network structure, self-organization, and the growth of international collaboration in science.<br>10.1016/j.respol.2005.08.002</td><td>614</td></tr><tr><td>Mingers J, 2015, Eur J Oper Res</td><td>A review of theory and practice in scientometrics.<br>10.1016/j.ejor.2015.04.002</td><td>426</td></tr><tr><td>Leydesdorff L, 2009, J AM SOC INF SCI TEC-a-b-c</td><td>A global map of science based on the ISI subject categories.<br>10.1002/asi.20967</td><td>393</td></tr><tr><td>Zhou P, 2006, Res policy</td><td>The emergence of China as a leading nation in science.<br>10.1016/j.respol.2005.08.006</td><td>385</td></tr><tr><td>Leydesdorff L, 2007, J AM SOC INF SCI TEC</td><td>Betweenness centrality as an indicator of the interdisciplinarity of scientific journals.<br>10.1002/asi.20614</td><td>347</td></tr><tr><td>Ràfols I, 2012, Res policy</td><td>How journal rankings can suppress interdisciplinary research: A comparison between Innovation Studies and Business & Management.<br>10.1016/j.respol.2012.03.015</td><td>335</td></tr><tr><td>Leydesdorff L, 2012, J Knowl Econ</td><td>The Triple Helix, Quadruple Helix, ..., and an N-Tuple of Helices: Explanatory models for analyzing the knowledge-based economy?<br>10.1007/s13132-011-0049-4</td><td>307</td></tr><tr><td>Ràfols I, 2010, J AM SOC INF SCI TEC</td><td>Science overlay maps: A new tool for research policy and library management</td><td>290</td></tr><tr><td>Leydesdorff L, 2006, J AM SOC INF SCI TEC</td><td>Co-occurrence matrices and their applications in information science: Extending ACA to the web environment</td><td>270</td></tr></tbody></table>

As can be seen in the results of Table 7, the article "The dynamics of innovation: from National Systems and "Mode 2" to a Triple Helix of university-industry-government relations" (Etzkowitz; Leydesdorff, 2000) has received the highest number of citations, followed by the article "Network structure, self-organization, and the growth of international collaboration in science" (Wagner; Leydesdorff, 2005) y "A review of theory and practice in scientometrics" (Mingers; Leydesdorff, 2015). Based on the content analysis of the best research articles, three themes are identified: 3 of the 10 articles focused on the Triple Helix, 3 of the 10 focused on scientometrics, and 1 of the 10 focused on a global map of science. (Leydesdorff; Ràfols, 2009).

<figure><img src="image_12.png" /><figcaption>Figure 6. Word cloud based on author keywords</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>Figure 7. Keywords plus treemap.</figcaption></figure>

## 3.2. Research topics and keyword trends

In this section we present the results to answer the question: what are the most common research topics and keyword trends in Leydesdorff publications? We present a thematic analysis to detect the main research topics in the field using a word cloud and a word treemap.

Figure 6 shows the word cloud for the 50 most common author keywords in the collection of publications. The size of the keyword in the figure indicates the frequency of the keyword in the dataset. As can be seen in the figure, the most frequently used words determine the content of most of the studies in the collection. More specifically, the frequent keyword “triple helix” is the main theme, as the papers in the collection address various aspects of the triple helix of knowledge production, university-industry-government relations and perspectives on innovation systems. The keywords “bibliometrics”, “citation analysis”, “scientometrics”, “social network analysis”, “cited references” and “evaluation” show

<figure><img src="image_14.png" /><figcaption>Figure 8. Leydesdorff’s publication co-citation network</figcaption></figure>
<figure><img src="image_15.png" /><figcaption>Figure 9. Map of collaboration between authors from different countries</figcaption></figure>

their importance and represent the main methodologies according to their conceptual meaning in Leydesdorff’s publications and research.

The 50 most commonly used keywords in articles are presented in the form of a Treemap of words. The Treemap in Figure 7 highlights the combination of plus keywords, indicating triple helix and bibliometrics. “Triple helix” is the most used keyword, while “lock-in” is the least used. Focusing on the keywords, other research areas that were of interest are science, indicators, network maps, innovation and interdisciplinarity.

### 3.3. Co-citation network

In this subsection, results are presented to answer the question: What are the main groups of co-citations related to Leydesdorff’s publications?

Figure 8 shows the co-citation network, a type of network in which nodes represent scientific papers and links between nodes indicate that these papers have been cited together in the same reference work. This network was conducted with a minimum degree of co-citation equal to three and a threshold of 50 network nodes. The nodes were labelled with the first author and the year of publication of the article, while the network link is the co-citation between two documents. The node size indicates the number of citations received by the papers and the link thickness represents the strength of the co-citation links. The colour of the node shows the cluster with which the article is associated, in our case two: one related to bibliometrics and the other to scientific innovation.

### 3.4. Networking between countries

In this subsection, results are presented to answer the question: what is the network of collaboration between authors from different countries in Leydesdorff’s research?

Figure 9 shows such a map of international collaboration. It depicts the publication output of authors from each country and the collaboration between authors from different countries. Countries with a darker colour indicate more publications than countries with a lighter colour, while the thickness of the lines represents stronger collaborations between countries.

Figure 10 shows the collaborative social network at country level in detail. The node in the network represents the country and the link between two nodes represents the cooperation between countries. The size of the country indicates the degree of cooperation, and the

<figure><img src="image_16.png" /><figcaption>Figure 10. Cross-country collaboration network (graph generated with VOSifier)</figcaption></figure>
thickness of the link indicates the closeness of the collaboration between countries. It is worth highlighting the collaboration with authors from our country, consistent with the high number of publications by this author in the journal *Profesional de la información*.

## 4. Mapping scientific networks

The concept of “scientific network mapping” refers to the process of visualising and analysing the relationships and connections between different elements within the scientific domain, such as researchers, institutions, or subject areas. This practice uses network analysis tools to graphically represent the structure and dynamics of interactions in the scientific community.

In the context of scientific research, network mapping can reveal patterns of collaboration, identify centres of influence, and provide information on the interconnectedness between disciplines or areas of study. Methods employed include social network analysis, where nodes represent entities such as researchers or institutions, and links between nodes represent collaborative relationships, citations, or any other form of relevant interaction.

This approach helps to understand the structure and evolution of scientific communities, facilitating the identification of key research areas, the assessment of the impact of researchers and institutions, and the visualisation of interdisciplinarity in scientific production. Scientific network mapping is valuable for analysing and communicating the complexity of interactions in academia.

### 4.1. Leydesdorff publications on scientific network mapping

Loet Leydesdorff is recognised for his significant contributions to the mapping of scientific networks (29 publications, see Table 8). He has developed innovative methodologies and tools to analyse and visualise the structure of scientific collaborations at different scales. Here are some key points about his work in this field:

1. *Intermediation centrality*: In his 2007 article, Leydesdorff proposes the use of “betweenness centrality” as an indicator of the interdisciplinarity of scientific journals. Betweenness centrality measures the frequency with which a node is on the shortest path between two other nodes in a network. He applied this measure to assess how scientific journals can serve as bridges between different disciplines, providing a means to map interdisciplinary connections (*Leydesdorff*, 2007a).

2. *Social network analysis*: Leydesdorff used social network analysis methods to explore collaborations between researchers and institutions. These analyses can visually map connections and relationships between actors in the scientific domain, revealing network structure and key points of collaboration.

3. *Bibliometric indicators*: In addition to mapping collaborations, Leydesdorff has developed bibliometric indicators to assess the impact and visibility of researchers and institutions. These indicators can be used to understand the distribution of collaborations and the influence of publications within the scientific network.

4. *Network visualisation*: In his 2009 paper, Leydesdorff presented visualisation methods for graphically representing scientific networks. These visualisations offer an intuitive insight into the distribution of collaborations and the overall structure of the scientific research network. (*Leydesdorff; Ràfols, 2009*).

<table><caption>Table 8. Leydesdorff's most relevant publications related to "mapping scientific networks"</caption><thead><tr><td>Thematic area</td><td>Subject - Cite</td></tr></thead><tbody><tr><td>Patent portfolio analysis of cities: statistics and maps of technological inventiveness</td><td>Cities and knowledge-based economy (Kogler; Heimeriks; Leydesdorff, 2018)</td></tr><tr><td>Betweenness and diversity in journal citation networks as measures of interdisciplinarity - A tribute to Eugene Garfield</td><td>Interdisciplinary journal ranking (Leydesdorff; Wagner; Bornmann, 2018)</td></tr><tr><td>Mapping patent classifications: portfolio and statistical analysis, and the comparison of strengths and weaknesses</td><td>Cooperative patent classifications (CPC) (Leydesdorff; Kogler; Yan, 2017)</td></tr><tr><td>Journal portfolio analysis for countries, cities, and organizations: Maps and comparisons</td><td>Web of Science data for portfolio analysis (Leydesdorff; Heimeriks; Rotolo, 2016)</td></tr><tr><td>Journal maps, interactive overlays, and the measurement of interdisciplinarity on the basis of Scopus data (1996-2012)</td><td>Global map of science using Scopus (Leydesdorff; De-Moya-Anegón; Guerrero-Bote, 2015)</td></tr><tr><td>International collaboration in science: the global map and the network</td><td>Global network of international co-authorship (Leydesdorff; Wagner; Park; Adams, 2013)</td></tr><tr><td>Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks</td><td>Preferential attachment in coauthorship networks (Abbasi; Hossain; Leydesdorff, 2012)</td></tr><tr><td>Mapping (USPTO) patent data using overlays to Google Maps</td><td>Patent-based Google Maps (Leydesdorff; Bornmann, 2012)</td></tr><tr><td>Mapping excellence in the geography of science: An approach based on Scopus data</td><td>Mapping centers of excellence worldwide (Bornmann; Leydesdorff; Walch-Solimena; Ettl, 2011)</td></tr><tr><td>'Meaning' as a sociological concept: A review of the modeling, mapping and simulation of the communication of knowledge and meaning</td><td>Discursive knowledge and communication (Leydesdorff, 2011)</td></tr></tbody></table>
<table><thead><tr><td>Thematic area</td><td>Subject - Cite</td></tr></thead><tbody><tr><td>The semantic mapping of words and co-words in contexts</td><td>Measuring semantics using latent semantic analysis (Leydesdorff; Welbers, 2011)</td></tr><tr><td>Science overlay maps: A new tool for research policy and library management</td><td>Science overlay maps for benchmarking (Rafols; Porter; Leydesdorff, 2010)</td></tr><tr><td>Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes</td><td>Overlaying scientific networks on geographic maps (Leydesdorff; Persson, 2010)</td></tr><tr><td>Maps on the basis of the Arts &amp; Humanities Citation Index: The journals Leonardo and Art journal versus "digital humanities" as a topic</td><td>Mapping Arts &amp; Humanities Citation Index (A&amp;HCI) (Leydesdorff; Salah, 2010)</td></tr><tr><td>Journal maps on the basis of Scopus data: A comparison with the Journal Citation Reports of the ISI</td><td>Comparing Scopus and Journal Citation Reports (Leydesdorff; De-Moya-Anegón; Guerrero-Bote, 2010)</td></tr><tr><td>Knowledge linkage structures in communication studies using citation analysis among communication journals</td><td>Mapping communication studies (Park; Leydesdorff, 2009)</td></tr><tr><td>Dynamic animations of journal maps: Indicators of structural changes and interdisciplinary developments</td><td>Dynamic analysis of structural change in sciences (Leydesdorff; Schank, 2008)</td></tr><tr><td>Korean journals in the Science Citation Index: What do they reveal about the intellectual structure of S&amp;T in Korea?</td><td>South Korea's research output (Park; Leydesdorff, 2008)</td></tr><tr><td>Betweenness centrality as an indicator of the interdisciplinarity of scientific journals</td><td>Centrality measures in journal citation networks (Leydesdorff, 2007a)</td></tr><tr><td>Mapping interdisciplinary at the interfaces between the science citation index and the social science citation index</td><td>Combining journal citation reports (Leydesdorff, 2007)</td></tr><tr><td>Clustering methodologies for identifying country core competencies</td><td>Mexican science and technology literature (Kostoff; Del-Rio; Cortés; Smith; Smith; Wagner; Leydesdorff; Karypis; Malpohl; Tshiteya, 2007)</td></tr><tr><td>Mapping the Chinese Science Citation Database in terms of aggregated journal-journal citation relations</td><td>Mapping Chinese Science Citation Database (Leydesdorff; Jin, 2005)</td></tr><tr><td>Mapping the Chinese Science Citation Database</td><td>Mapping Chinese Science Citation Database (alternative abstract) (Leydesdorff; Bihui, 2004)</td></tr><tr><td>Clusters and maps of science journals based on bi-connected graphs in Journal Citation Reports</td><td>Decomposing journal-journal citation matrix (Leydesdorff, 2004)</td></tr><tr><td>Why words and co-words cannot map the development of the sciences</td><td>Word co-occurrence analysis in biochemistry (Leydesdorff, 1997)</td></tr><tr><td>Mapping change in scientific specialties: A scientometric reconstruction of the development of artificial intelligence</td><td>Emergence of artificial intelligence as a discipline (Van-den-Besselaar; Leydesdorff, 1996)</td></tr><tr><td>Tracking areas of strategic importance using scientometric journal mappings</td><td>Indicators for tracking emerging developments (Leydesdorff; Cozzens; Van-den-Besselaar, 1994)</td></tr><tr><td>Various methods for the mapping of science</td><td>(Leydesdorff, 1987)</td></tr></tbody></table>

## 4.2. The Cosma software

Cosma¹ (https://cosma.arthurperret.fr) was developed as part of the ANR HyperOtlet programme, which aimed to represent Paul Otlet's social network in the form of an interactive graph, known as Otletosphere (https://hyperotlet.huma-num.fr/otletosphere). Cosma was developed by Guillaume Brioudes, Olivier Le Deuff and other collaborators in 2021.

It is a free experimental research tool, published under a free licence, which offers an innovative way to visualise and explore documentary networks.

Main features of Cosma:

1. Graph visualisation: allows the visualisation of an interactive documentary graph. The nodes of the network represent countries and the links between the nodes represent the cooperation between the authors of these countries.

2. Navigation functionalities: Cosma's interface is divided into three zones. A panel on the left contains navigation functions such as search, index and display filters. On the right, a panel displays the selected record with a bibliography automatically generated from the sources cited in the text of the record.

3. Data export: Unlike most visualisation tools, Cosma inverts the usual logic. The application part, called cosmograph, is a simple creation form. The created export, an HTML file called cosmoscope, constitutes the actual visualisation interface. This HTML file can be exported, used and shared independently.

4. Discussion support: Cosmoscope files can be shared, making them a support for discussion in the context of a research or teaching assignment.

5. Recognition of categorisation: Cosma recognises, from a previous analysis, the categorisation of the cards and associates graphic codes (colours, layouts) and interactions (filtering of displayed elements) to them.
<figure><img src="image_17.png" /><figcaption>Figure 11. Cosma interface
https://cosma.arthurperret.fr</figcaption></figure>

## 4.3. Stages of analysis of Loet Leydesdorff’s mapping of scientific networks

Scientific mapping attempts to find representations of the intellectual connections within the dynamically changing system of scientific knowledge (Small, 1997). In other words, scientific mapping shows the structural and dynamic aspects of scientific research (Cobo et al., 2011). In this paper we have developed a mapping of the publications of L. Leydesdorff who, throughout his career, has been one of the pioneers of this type of research.

The scientific mapping we have produced is a visual representation of how disciplines, fields, documents, co-authors, author words and index words (**keywords plus**) relate to each other in Leydesdorff publications.

In this section we describe the different stages of analysis of this mapping:

(a) **Source of data:** For this mapping, publication data were retrieved from the *Web of Science (WoS) Core Collection* database. Our dataset contains 424 articles published between 1980 and 2023.

(b) **The units of analysis:** From the 424 documents we selected the references of the publications, the co-authors, the title, the abstract. In addition, we selected the original keywords of the documents (author keywords) and the indexing keywords provided by the database (*ISI Keywords Plus*) as words to be analysed. We also took the *WoS* subject categories, the Orcid of the co-authors and the DOI of the publication.

(c) **Data pre-processing:** A scientific mapping analysis cannot be applied directly to data retrieved from bibliographic sources, i.e. a pre-processing of the retrieved data is necessary. Thus, the pre-processing of the data has been as follows:

- The correction and addition of the names of certain co-authors, and the inclusion of their photo in the database.

- Detection of duplicate elements and misspellings of co-authors and author words and index words.

- The division of the articles into different time sub-periods, in order to analyse the evolution of Leydesdorff’s research (see table).

(d) **Standardisation process:** The Cosma software uses a specific visualisation algorithm to graphically represent the relationships between documentary elements. This algorithm is called a "cosmograph".

(e) **Methods of analysis:** Before applying the visualisation, Cosma performs a preliminary analysis to categorise the document files. This analysis determines the assignment of graphic codes such as colours and layouts.

(f) **Display algorithm:** force-layout algorithm, which Cosma incorporates.

As a final result, our Leydesdorff cosmoscope is available for use at this URL:
http://metroteach.com/Leydesdorff/index.html

It can be downloaded by clicking on the link Made with Cosma - About at the bottom left of the interface.
http://metroteach.com/Leydesdorff/cosmoscopio.html

The interface allows switching to a timeline visualisation (Table 9) to show the changes that occur with this variable (by clicking on the Timeline mode checkbox).
<figure><img src="image_18.png" /><figcaption>Figure 12. Scientific network mapping of Leydesdorff's publications.
http://metroteach.com/Leydesdorff/index.html</figcaption></figure>

<figure><img src="image_19.png" /><figcaption>Figure 13. Discharge line of the Leydesdorff cosmoscope.
http://metroteach.com/Leydesdorff/cosmoscopio.html</figcaption></figure>
<figure><img src="image_20.png" /><figcaption>Figure 14. Leydesdorff cosmoscope " timeline" option</figcaption></figure>

<table><caption>Table 9. Timeline of publications</caption><tr><td>1980</td><td>1983</td><td>1987</td></tr><tr><td>1995</td><td>1999</td><td>2003</td></tr><tr><td>2007</td><td>2011</td><td>2015</td></tr><tr><td>2019</td><td>2023</td><td>Ayuda de Cosma</td></tr></table>
## 5. Conclusions

A bibliometric analysis of Leydesdorff's publications collected in WoS has been carried out and a scientific mapping of his papers, including co-authors, their countries of origin and keywords (author and indexing), has also been produced.

The literature review on Loet Leydesdorff highlights his significant contributions to the sociology of science, bibliometric analysis, science communication and scientific network mapping. His work continues to influence and guide research in these areas, demonstrating the breadth of his intellectual impact.

For the mapping of scientific output we have included different methods of analysis (although some of them are common), which allowed us to discover the different facets of the knowledge investigated by Leydesdorff. Since the visualisations are different in each of them, different views of the field can be generated to help interpret and analyse the results. This cooperation between tools leads to a positive synergy, which allows extracting the knowledge hidden behind the data.

Our work has been intended as a small tribute to this recently deceased scientist, who has contributed to the advancement of several areas of study. We believe that a more complete scientific mapping analysis of Leydesdorff's work should be carried out, including the publications that WoS does not include, in order to compile all the knowledge, important theoretical contributions and the different perspectives (intellectual, social or conceptual) of the author's different areas of research.

## 6. Note

1. The name Cosma comes from Cosmas Rosellius, a Florentine Dominican monk, author of a *Thesaurus artificiosæ moriæ* (1579), which translates as “treasure of artificial memory”. A feature of Rossellius’ book is the mnemonic verses given to help memorize orders of places, whether orders of Hell, or the order of the signs of the zodiac.
https://archive.org/download/thesaurusartifi00padogoog/thesaurusartifi00padogoog.pdf

## 7. References

Abbasi, Aliresa; Hossain, Liaquad; Leydesdorff, Loet (2012). "Betweenness centrality as a driver of preferential attachment in the evolution of research collaboration networks". *Journal of informetrics*, v. 6, n. 3.
https://doi.org/10.1016/j.joi.2012.01.002

Aria, Massimo; Cuccurullo, Corrado (2017). "Bibliometrix: An R-tool for comprehensive science mapping analysis". *Journal of informetrics*, v. 11, n. 4.
https://doi.org/10.1016/j.joi.2017.08.007

Bornmann, Lutz; Leydesdorff, Loert; Walch-Solimena, Christiane; Ettl, Christoph (2011). "Mapping excellence in the geography of science: An approach based on Scopus data". *Journal of informetrics*, v. 5, n. 4.
https://doi.org/10.1016/j.joi.2011.05.005

Cobo, Manuel J.; López-Herrera, Antonio-Gabriel; Herrera-Viedma, Enrique; Herrera, Francisco (2011). "Science mapping software tools: Review, analysis, and cooperative study among tools". *J. Assoc. Inf. Sci. Technol.*, v. 62, pp. 1382-1402.

Donthu, Naveen; Kumar, Satish; Mukherjee, Debmalya; Pandey, Nitesh; Lim, Weng-Marc (2021). "How to conduct a bibliometric analysis: An overview and guidelines". *Journal of business research*, v. 133.
https://doi.org/10.1016/j.jbusres.2021.04.070

Etzkowitz, Henry; Leydesdorff, Loet (1996). "A triple helix of academic-industry-government relations: Development models beyond 'capitalism versus socialism'". *Current science*, v. 70, n. 8.

Etzkowitz, Henry; Leydesdorff, Loet (2000). "The dynamics of innovation: from National Systems and 'Mode 2' to a Triple Helix of university-industry-government relations". *Research policy*, v. 29, n. 2.
https://doi.org/10.1016/S0048-7333(99)00055-4

Kogler, Dieter-Franz; Heimeriks, Gaston; Leydesdorff, Loet (2018). "Patent portfolio analysis of cities: statistics and maps of technological inventiveness". *European planning studies*, v. 26, n. 11.
https://doi.org/10.1080/09654313.2018.1530147

Kostoff, Ronald N.; Del-Río, J. Antonio; Cortés, Héctor D.; Smith, Charles; Smith, Andrew; Wagner, Caroline; Leydesdorff, Loet; Karypis, George; Malpohl, Guido; Tshiteya, Rene (2007). "Clustering methodologies for identifying country core competencies". *Journal of information science*, v. 33, n. 1.
https://doi.org/10.1177/0165551506067124

Leydesdorff, Loet (1979). "Dynamic and stochastic models for reciprocal citation processes" (Thèse de doctorat, Université d'Amsterdam).

Leydesdorff, Loet (2007). "Betweenness centrality as an indicator of the interdisciplinarity of scientific journals". *Journal of the American Society for Information Science and Technology*, v. 58, n. 9.
https://doi.org/10.1002/asi.20614
Leydesdorff, Loet (2001). "A sociological theory of communication; The self-organization of the knowledge-based Society". Universal Publishers / upublish.com, USA.
https://www.universal-publishers.com/m/book.php?method=ISBN&book=1581126956

Leydesdorff, Loet (1987). "Various methods for the mapping of science". Scientometrics, v. 11, n. 5-6.
https://doi.org/10.1007/BF02279351

Leydesdorff, Loet (1997). "Why words and co-words cannot map the development of the sciences". Journal of the American Society for Information Science, v. 48, n. 5.

Leydesdorff, Loet (2004). "Clusters and maps of science journals based on bi-connected graphs in Journal Citation Reports". Journal of documentation, v. 60, n. 4.
https://doi.org/10.1108/00220410410548144

Leydesdorff, Loet (2007). "Mapping interdisciplinarity at the interfaces between the science citation index and the social science citation index". Scientometrics, v. 71, n. 3.
https://doi.org/10.1007/s11192-007-1694-z

Leydesdorff, Loet (2007). "Betweenness centrality as an indicator of the interdisciplinarity of scientific journals". Journal of the American Society for Information Science and Technology, v. 58, n. 9.
https://doi.org/10.1002/asi.20614

Leydesdorff, Loet (2011). "'Meaning' as a sociological concept: A review of the modeling, mapping and simulation of the communication of knowledge and meaning". Social science information sur les sciences sociales, v. 50, n. 3-4.
https://doi.org/10.1177/0539018411411021

Leydesdorff, Loet; Bihui, Jin (2004). "Mapping the Chinese science citation database". In: University of Amsterdam, v. 41.
https://doi.org/10.1002/meet.1450410157

Leydesdorff, Loet; Bihui, Jin (2005). "Mapping the Chinese Science Citation Database in terms of aggregated journal-journal citation relations". Journal of the American Society for Information Science and Technology, v. 56, n. 14.
https://doi.org/10.1002/asi.20209

Leydesdorff, Loet; Bornmann, Lutz (2012). "Mapping (USPTO) patent data using overlays to Google Maps". Journal of the American Society for Information Science and Technology, v. 63, n. 7.
https://doi.org/10.1002/asi.22666

Leydesdorff, Loet; Cozzens, Susan; Van-den-Besselaar, Peter (1994). "Tracking areas of strategic importance using scientific journal mappings". Research policy, v. 23, n. 2.
https://doi.org/10.1016/0048-7333(94)90054-X

Leydesdorff, Loet; De-Moya-Anegón, Félix; Guerrero-Bote, Vicente P. (2010). "Journal maps on the basis of Scopus data: A comparison with the Journal Citation Reports of the ISI". Journal of the American Society for Information Science and Technology, v. 61, n. 2.
https://doi.org/10.1002/asi.21250

Leydesdorff, Loet; De-Moya-Anegón, Félix; Guerrero-Bote, Vicente P. (2015). "Journal maps, interactive overlays, and the measurement of interdisciplinarity on the basis of Scopus data (1996-2012)". Journal of the Association for Information Science and Technology, v. 66, n. 5.
https://doi.org/10.1002/asi.23243

Leydesdorff, Loet; Heimeriks, Gaston; Rotolo, Daniele (2016). "Journal portfolio analysis for countries, cities, and organizations: Maps and comparisons". Journal of the Association for Information Science and Technology, v. 67, n. 3.
https://doi.org/10.1002/asi.23551

Leydesdorff, Loet; Kogler, Dieter-Franz; Yan, Bowen (2017). "Mapping patent classifications: portfolio and statistical analysis, and the comparison of strengths and weaknesses". Scientometrics, v. 112, n. 3.
https://doi.org/10.1007/s11192-017-2449-0

Leydesdorff, Loet; Meyer, Martin (2010). "The decline of university patenting and the end of the Bayh-Dole effect". Scientometrics, v. 83, n. 2.
https://doi.org/10.1007/s11192-009-0001-6

Leydesdorff, Loet; Persson, Olle (2010). "Mapping the geography of science: Distribution patterns and networks of relations among cities and institutes". Journal of the American Society for Information Science and Technology, v. 61, n. 8.
https://doi.org/10.1002/asi.21347

Leydesdorff, Loet; Ràfols, Ismael (2009). "A global map of science based on the ISI Subject Categories". Journal of the American Society for Information Science and Technology, v. 60, n. 2.
https://doi.org/10.1002/asi.20967
Leydesdorff, Loet; Salah, Alkim-Almila-Akdag (2010). "Maps on the basis of the *Arts & Humanities Citation Index*: The journals *Leonardo* and *Art Journal* versus 'digital humanities' as a topic". *Journal of the American Society for Information Science and Technology*, v. 61, n. 4.
https://doi.org/10.1002/asi.21303

Leydesdorff, Loet; Schank, Thomas (2008). "Dynamic animations of journal maps: Indicators of structural changes and interdisciplinary developments". *Journal of the American Society for Information Science and Technology*, v. 59, n. 11.
https://doi.org/10.1002/asi.20891

Leydesdorff, Loet; Wagner, Caroline S.; Bornmann, Lutz (2018). "Betweenness and diversity in journal citation networks as measures of interdisciplinarity - A tribute to Eugene Garfield". *Scientometrics*, v. 114, n. 2.
https://doi.org/10.1007/s11192-017-2528-2

Leydesdorff, Loet; Wagner, Caroline S.; Park, Han-Woo; Adams, Jonathan (2013). "International collaboration in science: the global map and the network". *Profesional de la informacion*, v. 22, n. 1.
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Leydesdorff, Loet; Welbers, Kasper (2011). "The semantic mapping of words and co-words in contexts". *Journal of informetrics*, v. 5, n. 3.
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