Trust, quality, and the network collection experience: A tale of two studies on the Democratic Republic of the Congo

Data collection in social network research has advanced to include online questionnaires, digital metadata mining of internet sites, and the use of remote-sensing technologies. Some scholars however call for more attention to nuanced understandings of ties and contexts in studies of social structure and relationships, evoking practices that characterise the field’s foundational works. This article’s two studies reference these earlier efforts, drawing on ethnography and primary data collection. Both were undertaken in conflict-affected eastern Democratic Republic of the Congo (DRC) and broadly aimed to refine understandings of public authority and governance. Such research strives to inform humanitarian interventions to support social structures and actors which benefit their communities – however unexpected and unconventional. The first study (2016) employed a novel link-tracing design to examine personal support networks entwining purportedly hostile sub-populations, from combatants to unaffiliated civilians. The second (2018−20) focussed on access to essential social services across different governance arrangements, areas dominated by tenuous alliances of domestic or foreign militias and other actors. Leveraging an egocentric network design, it yielded multilevel relational network chain data. Each study was rife with obstacles related to accessing participants, sampling, reliability, and validity. We reflect on this network collection experience, foregrounding the interdependence between trust and data quality brought into stark relief by the setting’s instability and insecurity. This interdependency impacts all social network research, especially when it involves precarious contexts or sensitive topics.