Social movement scholars are increasingly interested in Internet activism but have struggled to find robust methods for identifying cases, particularly representative samples of online protest content, given that no population list exists. This article reviews early approaches to this problem, focusing on three recent case sampling designs that attempt to address this problem. The first approach purposively samples from an organizationally based sampling frame. The second approach randomly samples from a SMO-based sampling frame. The third approach mimics user routines to identify populations of "reachable" websites on a given topic, which are then randomly sampled. For each approach, I examine the sampling frame and sampling method to understand how cases were selected, outline the assumptions built into the overall sampling design, and discuss an exemplary research project employing each design. Comparisons of findings from these exemplar studies indicate that sampling designs are extremely consequential. I close by recommending best practices.

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