The structure and dynamics of networks of scientific collaborations in Northern Africa


We examine the structure and dynamics of network of scientific international collaborations within North Africa (Morocco, Algeria, Tunisia and Egypt) using both publishing and patent data. Results show that the region has undergone a sustained process of internationalization, which has translated in both an expansion of the network of scientific collaborations and a relative increase in the research output of international teams. At the same time we find the existence of a very limited degree of scientific integration at the regional level, i.e. within Northern Africa. Among the countries examined, Egypt seems to be the most active one in terms of size of research output as well as number and variety of international collaborations. Moreover, Egypt is the most central node of the regional research network and this centrality has considerably grown over time. This increased importance of Egypt as regional research hub is associated with a remarkable increase in the centrality of Saudi Arabia within Egypt’s research network. This holds across a variety of research fields as well as in terms of applied science (as shown by patent data). Overall, these results suggest that the region is undergoing a deep transformation in the structure and composition of scientific collaborations.

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  1. 1.

    Information on team composition is retrieved from the publication matrix described above. In particular, for each year, we count the number of articles satisfying conditions (1), (2) and (3) and then divide each figure by the total number of articles published that year.


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Correspondence to Fabio Landini.



Network analysis

Our original data comes with the format depicted in Table 2, where each row keeps track of the country-specific affiliations of the authors. The columns refer to the variables that we use to construct the publication matrix (other variables such as the FOS sector are not displayed), namely:

Table 2 Entry table
  • sourceyear: the year in which the article was published;

  • NATIONCODE: the code of the countries which the authors are affiliated;

  • AUTHCOUNT: the number of authors that wrote the articles;

  • Artcount: the article ID.

In this simplified example we assume that there is only 1 year (2003) and that there are only three articles and five countries (the original entry table is obviously more complex spanning over 11 years, 97,066 articles and 209 countries). The first article (Artcount = 1) is co-authored by three authors (AUTHCOUNT = 3) coming from countries 1, 4 and 5 [NATIONCODE(1) = 1, NATIONCODE(2) = 4, NATIONCODE(3) = 5]. The second article (Artcount = 2) is co-authored by two authors (AUTHCOUNT = 2) coming from countries 1 and 2 [NATIONCODE(4) = 1, NATIONCODE(5) = 2]. The third article (Artcount = 3) is co-authored by two authors (AUTHCOUNT = 2) coming from countries 1 and 3 [NATIONCODE(6) = 1, NATIONCODE(7) = 2].

Given this entry table we use the following MATLAB® routine to construct the publication matrix (the lines of code are reported in bold whereas the comments are reported in italics after the symbol “ %”):

n_country=5; % Set the number of countries equal to 5.

[n_lines, z]=size(Artcount); % Set the number of lines in the entry table equal to the size of vector Artcount, i.e. 7.

n_art=3; % Set the number of articles equal to 3.

Art_Country_03=zeros(n_art,n_country); % Construct a country by publication matrix (Art_Country_03) filled with zeros where each row corresponds to one article and each column to one country. That is:


end % This for loop goes through each line of the entry table. If the sourceyear is equal to 2003 and the number of authors is greater than 2 and smaller than 800 (to control for outliners) we add 1 in the cell of the publication matrix that corresponds to the article ID (Artcount) and the country code (NATIONCODE). In particular, the resulting publication matrix after each step of the for loop is the following:


Net_Country_03=Art_Country_03′*Art_Country_03; %The country by country adjacency matrix (Net_Country_03) is then derived by multiplying the transpose of the publication matrix by the original matrix.

Country abbreviations

See Table 3.

Table 3 Country abbreviation

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Landini, F., Malerba, F. & Mavilia, R. The structure and dynamics of networks of scientific collaborations in Northern Africa. Scientometrics 105, 1787–1807 (2015).

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  • Research collaboration
  • Scientific research
  • North Africa
  • Patents
  • Network analysis

JEL Classification

  • C80 (data collection and data estimation methodology: general)
  • O10 (economic development: general)
  • O55 (economywide country studies: Africa)