EAGER: Identifying Methodological and Ethical Challenges in Online Research of Hard-to-Reach Populations during the COVID-19 pandemic

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The COVID-19 pandemic has necessitated the retooling of techniques for collecting human behavioral data, in ways that present new challenges to the reliability and validity of that data. But it has also provided an opportunity for innovating methods of data collection and analysis, particularly with respect to the analysis of social networks. This project pilots a new methodological technique, asking whether digital platforms have a higher degree of efficacy in engaging more vulnerable populations. Findings from this research will disseminated in a way that aims to benefit public health efforts. This scientific study will also broaden the participation of the underrepresented groups in the co-production of scientific knowledge. The broader scientific question proposed is whether valid and reliable data can be gathered virtually from a marginalized population. It pilots a new digital ethnographic method for identifying social networks among marginalized populations by coupling the social network mapping of personal (egocentric) social networks with qualitative data collection methods (semi-structured interviews that are focused on ensuring data valid through the building of rapport between research participants and the research team, and observational techniques within social media and other online platforms). If the combination of social network analysis (SNA) and digital ethnographic techniques can reliably yield valid data for marginalized/stigmatized populations, digital venues may prove to be a safer and more efficient space for engaging with vulnerable populations, which in turn may potentially allow for the rapid accumulation of data of hard-to-reach populations. This exploratory project intends to make methodological contributions to social science research methods in regards to studying hidden/marginalized populations through the identification of network properties, cluster boundaries, and the social spaces of various marginalized groups. As a result, this project will enhance the intellectual debates on social network theories and methodology, and may come to serve as a model by providing alternative research methods to study hard-to-reach populations.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.