Abstract
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.
Abstract (translated)
社交网络分析（SNA）是一套在社会科学和行为科学研究领域开发的技术，用于描述和分析一组个体之间的社交关系。在构建执行SNA分析的社交网络时，首先完成了一个数据收集过程，以提取个体的特征以及他们之间的关系。这通常是通过完成包含不同类型问题的问卷来完成的。然后，存在许多不同的可能网络生成问题以及对应特征和关系的许多可能性。这些问题（问题的提出方式，对每个答案的权重等）中可能引入许多变化，这些变化可能影响结果的网络。由于过程费时且容易出错，因此很难手动实现这些不同变化。本文中所述的工具使用了语义知识表示技术，以便促进这种类型的敏感性研究。工具的基础是一个概念结构，称为“本体论”，它能够表示不同概念及其定义。工具与其他类似工具进行了比较，强调了这种方法的优势，并给出了一个关于青少年饮酒消费习惯的正在进行SNA研究的具体例子。
URL
https://arxiv.org/abs/2402.12390
