Sources and data for social network analysis. Social network analysis (SNA) is becoming more and more widespread in several scientific disciplines as a method for processing social, economic, geographic, historical, digital, etc. data. Visualizations of graphs, communities and other ties are multiplying. However, there is a risk that SNA users may lose sight of the conditions under which their data are produced and thereby over-interpret or under-interpret the results. This article provides a guide to the different types of sources of network data, and the pitfalls and choices encountered in the process of producing network data. The first part provides an overview of these pitfalls and choices, and the second part focuses on the specifics of each source of data. Based on the authors’ experience in training network researchers, the article proposes a review of controlled ways of producing network data from this array of sources.

社交网络分析的来源和数据。社交网络分析 (SNA) 作为一种处理社会、经济、地理、历史、数字等数据的方法，在多个科学学科中变得越来越普遍。图表、社区和其他联系的可视化正在成倍增加。然而，存在这样一种风险，即 SNA 用户可能会忽视产生其数据的条件，从而过度解释或低估结果。本文提供了不同类型的网络数据来源的指南，以及在生产网络数据过程中遇到的陷阱和选择。第一部分概述了这些陷阱和选择，第二部分重点介绍了每个数据源的细节。基于作者在培训网络研究人员方面的经验，