  Alcohol Use Disorder (AUD) is a major concern for public health organizations
worldwide, especially as regards the adolescent population. The consumption of
alcohol in adolescents is known to be influenced by seeing friends and even
parents drinking alcohol. Building on this fact, a number of studies into
alcohol consumption among adolescents have made use of Social Network Analysis
(SNA) techniques to study the different social networks (peers, friends,
family, etc.) with whom the adolescent is involved. These kinds of studies need
an initial phase of data gathering by means of questionnaires and a subsequent
analysis phase using the SNA techniques. The process involves a number of
manual data handling stages that are time consuming and error-prone. The use of
knowledge engineering techniques (including the construction of a domain
ontology) to represent the information, allows the automation of all the
activities, from the initial data collection to the results of the SNA study.
This paper shows how a knowledge model is constructed, and compares the results
obtained using the traditional method with this, fully automated model,
detailing the main advantages of the latter. In the case of the SNA analysis,
the validity of the results obtained with the knowledge engineering approach
are compared to those obtained manually using the UCINET, Cytoscape, Pajek and
Gephi to test the accuracy of the knowledge model.
