On the Architecture of Semantic Networks: A Quantitative Assessment of Subjective Representations (Published)
The increased use of computer aided qualitative data analysis software in social research fields profit from the semantic networks (SN) for the data organization and analysis. However, the validation and scope of these methodologies remains as an open discussion. In the other hand, graph theory methods are a growing field on mathematics but is becoming also important in most research fields, such as social and human sciences. Regardless the similarity between SN and graph theory, no studies have accessed the quantitative architecture of the SN. Here, we explored by quantitative means the subjective component of SN architecture. Overall, differences in the metrics of the SN graphs and loss of global correlation across experts suggested that the topology of SN include a subjective component, important in differentiating cognitive processes between persons. Furthermore, the results suggest that methods such as triangulation should be considered in the analysis of qualitative data.