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1. Introduction Scientific journals evidence digital objects produced by their respective discursive communities. These objects maintain semantic relationships among themselves, objectified by the terms used as their keywords. The relationships between these terms may offer an objective method of netnographic analysis, capable of revealing the evolution of the appropriation of these terms by a community, their relations with each other and their domain. 2 Purpose To demonstrate the analytical possibilities of semantic latency relations between the keywords of the articles of the journal Information & Information. 3 Methodology Graph analysis provides solid mathematical tools for analyzing relationships between elements of a given context. Its high capacity for abstraction has made this instrument applicable to several types of problems, besides mathematics, such as in physics, biology, chemistry, sociology and metric studies of information (Oliveira, 2018). 4 The experiment The Information & Information magazine is published quarterly and has an A2 rating on the CAPES Qualis system. The terms extracted from 641 articles, between the years 2000 and 2017, were organized in 822 vertices and 3,057 edges. Their relationships were established according to the algorithm shown in figure 1. Figure 1: Keyword extraction algorithm. Source: Authors. 5 Results Applied the centrality and intermediation algorithms and a filter of 87%, we obtained a graph with the most significant keywords of the magazine (Figure 2). Figure 2: Graph of the main keywords of the journal Information & Information. Source: Authors. 6 Conclusions The result highlights the terminological structure operated by a discursive community, revealed by the analysis of the graph. An arrangement, a structure, among the scientific articles is evidenced, which can methodically subsidize netnographic works. |
