  Social Network Analysis (SNA) is a set of techniques developed in the field
of social and behavioral sciences research, in order to characterize and study
the social relationships that are established among a set of individuals. When
building a social network for performing an SNA analysis, an initial process of
data gathering is achieved in order to extract the characteristics of the
individuals and their relationships. This is usually done by completing a
questionnaire containing different types of questions that will be later used
to obtain the SNA measures needed to perform the study. There are, then, a
great number of different possible network generating questions and also many
possibilities for mapping the responses to the corresponding characteristics
and relationships. Many variations may be introduced into these questions (the
way they are posed, the weights given to each of the responses, etc.) that may
have an effect on the resulting networks. All these different variations are
difficult to achieve manually, because the process is time-consuming and error
prone. The tool described in this paper uses semantic knowledge representation
techniques in order to facilitate this kind of sensitivity studies. The base of
the tool is a conceptual structure, called "ontology" that is able to represent
the different concepts and their definitions. The tool is compared to other
similar ones, and the advantages of the approach are highlighted, giving some
particular examples from an ongoing SNA study about alcohol consumption habits
in adolescents.
