Respondent-driven sampling (RDS) is a network sampling technique typically employed for hard-to-reach populations when traditional sampling approaches are not feasible (e.g., homeless) or do not work well (e.g., people with HIV). In RDS, seed respondents recruit additional respondents from their network of friends. The recruiting process repeats iteratively, thereby forming long referral chains.

RDS is typically implemented face to face in individual cities. In contrast, we conducted Internet-based RDS in the American Life Panel (ALP), a web survey panel, targeting the general US population. We found that when friends are selected at random, as RDS methodology requires, recruiting chains die out. When self-selecting friends, self-selected friends tend to be older than randomly selected friends but share the same demographic characteristics otherwise.

Using randomized experiments, we also found that respondents list more friends when the respondent’s number of friends is preloaded from an earlier question. The results suggest that with careful selection of parameters, RDS can be used to select population-wide Internet panels and we discuss a number of elements that are critical for success.