Análisis de Dominios por Medio de la Visualización de Mapas de Grandes Dominios Científicos

Subject category cocitation (SCC) and its representation through social networks has been shown to be a well-suited technique for the visualization and analysis of large scientific domains. The combination of SCC and PathfinderNetworks (PFNET) with prune values r = ∞ and q = n - 1 highlights the salient structure of the analyzed domain. This paper examines both the possible loss of structural information in the peripheral zones as a consequence of PFNET aggressivity due to the radical pruning conditions established and how it is solved and enhanced through heliocentric or second-level maps. Despite the above, large scientific domain maps are a highly valuable tool due to its capability to show the development of a scientific domains over time, reveal differences and similarities among domains, as well as suggest potential trends in them.