A citation from a paper published in one journal to a paper published in another establishes a clear link between the journals: it shows that their respective contents are relevant to each other, and suggests a level of similarity between the two. In any given time period a journal tends to contain citations to many other journals, and those it cites the most should be those with which it is most closely related. Across a broad network, citation relationships contain information about which journals are related to others, and so can be used to examine the structure of literature and the links between different fields1–5. In this article I use 5 years of Scopus-indexed citation data to position 19,562 journals in a map of scholarly research, and use the resulting map to look at the position of, and interactions between, subject fields.

Mapping Scopus

The full set of 2006–2010 citations were extracted from a bibliometric version of the Scopus database as a list of relationships between two publications; and while this includes proceedings and other serials besides journals, I refer solely to journals for clarity. (For more information on bibliometric databases, see the last issue of Research Trends6.) The 2006–2010 restriction applies in two ways: not only must the papers citing other papers have been published in this time period, but so too the articles they cite. After excluding journal self-citations, this produced a list of 4,589,565 journal–journal citation relationships, covering 20,213 journals and 27,196,324 citations. (A citation relationship is a count of the citations made from one journal to another within the time period — and so a single citation relationship often represents more than a single citation.)

This full network of data was reduced in order successfully to map it out. Journal–journal citation relationships representing less than 1 percent of the citations made by the citing journal in this set of data were removed, and this resulted in a smaller network containing 19,562 journals (96.8 percent), linked by 377,729 citation relationships (8.2 percent) containing 11,857,165 citations (43.6 percent). These citation relationships were then used to create a network graph, using the Gephi program, in which nodes represent journals, and connecting lines (or edges) the relationships between them.

Gephi is a freeware graphing program7 which comes with a range of layout algorithms; the recently-developed ForceAtlas28 was selected as it can quickly position thousands of nodes, and features many properties to refine the graph layout. As with many layout algorithms, ForceAtlas2 is force-directed, which means that unrelated nodes in the network repel one another, while connected nodes attract one another. In this case, the magnitude of these forces was determined by the proportion of citations given by the citing journal to the cited journal out of citations given to all other journals in the network, in the time period 2006–2010. Given the method of reducing the data, edge weights take a value between 0.01 and 1.00, such that the higher the value, the stronger the force of attraction between the two journals. The two forces at work result in a graph which stabilizes over time, until it has reached equilibrium. Figure 1 shows the results of using ForceAtlas2 to lay out our network of 19,562 journals.

 

Figure 1A network of 19,562 journals, linked by 377,729 citation relationships containing 11,857,165 citations mapped using Gephi and the ForceAtlas2 layout algorithm. Each journal is a node (circle) in the map, and edges (lines) between these nodes represent citations from one to the other. Node size is proportional to the total number of citations received by that journal in the time period 2006–2010. Data source: Scopus.

In theory, this map has positioned journals so that related journals are close to one another, and unrelated journals are further apart. But how can this be tested? One option is to use an existing subject classification system, and Figure 2 shows the same map colored according to the subject classifications used by Scopus. There are 27 subject areas, and each is given a different color; journal nodes take the color of the subject area to which they are assigned, but only if they are uniquely assigned to a subject area (journals belonging to multiple subject areas remain gray).

Figure 2Each subject area is assigned a color, used to show journals belonging solely to that subject area. Data source: Scopus.

As this labeled map shows, related fields are positioned close to one another; the map can be used to view the position of each subject area in relation to the others — from the health sciences at the left, round the social sciences at the bottom to mathematics at the right, up to physics and chemistry, and round the biological sciences at the top. The most multidisciplinary fields are positioned towards the center of the map, as is clear by the patches of gray journals belonging to multiple fields.

Stuck in the middle with you

Once we have confidence in the layout of the map, we can use it to look at specific subject areas. Figures 3 and 4 show the journals assigned to Environmental Science, and to Physics and Astronomy, respectively. The two subject areas cover a similar area at the right side of the map, stretching almost from the top to the bottom; however, the Physics and Astronomy map shows a much tighter core of journals located at the right edge of the map, while Environmental Science journals do not cluster strongly in any given area. Not only is the subject area multidisciplinary, reaching across the boundaries of other subjects, but the journals within the field are not as closely related to one another as the journals within Physics and Astronomy.

Figure 3 – All journals assigned to Environmental Science. Data source: Scopus.

Figure 4 – All journals assigned to Physics and Astronomy. Data source: Scopus.

Our global map can also be used to look at the crossover between multiple subject areas. Figure 5 again shows Environmental Science journals, and those in Physics and Astronomy, but this time combined with Earth and Planetary Science journals. Each subject area is given a primary color, and secondary and tertiary colors can be used to show the journals assigned to two or all three subject areas.

Figure 5 – Environmental Science journals are colored red; Earth and Planetary Science, yellow; and Physics and Astronomy, blue. Where journals are assigned to two of these subject areas, the secondary colors orange, green and purple are used; where all three, the tertiary color brown. Data source: Scopus.

Using this map to look at the position of the multi-subject journals, we can see that the Earth and Planetary/Environmental journals (in orange) are spread across a much wider area than the Earth and Planetary/Physics and Astronomy journals (in green), which cluster together very tightly. In addition, Earth and Planetary Science journals form a bridge between the other two subject areas.

A map of science formed using the citations indexed by Scopus allows for detailed analysis of not only where a single journal lies in the global map of literature, and the journals to which it is connected, but also the broader subjects that comprise the map, and journal sets that bridge disciplines.

References

1. Boyack, K.W. et al. (2005). Mapping the backbone of science. Scientometrics Vol. 64, pp. 351–374.
2. Boyack, K.W. et al. (2009). Mapping the structure and evolution of chemistry research. Scientometrics Vol. 79, pp. 45–60.
3. Leydesdorff, L. & Rafols, I. (2009). A global map of science based on the ISI subject categories. Journal of the American Society for Information Science and Technology Vol. 60, pp. 348–362.
4. Leydesdorff, L. et al. (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 Vol. 61, pp. 352–369.
5. Leydesdorff, L. & Rafols, I. (in press). Interactive overlays: a new method for generating global journal maps from Web-of-Science data. Journal of Informetrics.
6. Moed, H. F. et al. (2011). Is science in your country declining? Or is your country becoming a scientific super power, and how quickly? Research Trends, Issue 25.
7. Bastian, M. et al. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media.
8. Jacomy, M. et al. (2011). ForceAtlas2, a graph layout algorithm for handy network visualization.
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