Generalizability and Reproducibility of Search Engine Online User Studies

Research in interactive information retrieval (IR) usually relies on lab user studies or online ones. A key concern of these studies is the generalizability and reproducibility of the results, especially when the studies involved only a limited number of participants. The interactive IR community, however, does not have a commonly agreed guideline regarding how many participants should recruit. We study this fundamental research protocol issue by examining the generalizability and reproducibility of results with respect to a different number of participants using simulation-based approaches. Specifically, we collect a relatively large number of participants' observations for a representative interactive IR experiment setting from online user studies using crowdsourcing. We sample smaller numbers of participants' results from the collected observations to simulate the results of online user studies with a smaller scale. We empirically analyze the patterns of generalizability and reproducibility regarding different dependent variables and draw conclusions related to the optimal number of participants. Our study contributes to interactive information retrieval research by 1) establishing a methodology for evaluating the generalizability and reproducibility of results, and 2) providing guidelines regarding the optimal number of participants for search engine user studies.