A reliability analysis of Mechanical Turk data

Amazon's Mechanical Turk is an online labor market where requesters post jobs and workers choose which jobs to do for pay. The central purpose of this article is to demonstrate how to use this Web site for conducting behavioral research and to lower the barrier to entry for researchers who could benefit from this platform. We describe general techniques that apply to a variety of types of research and experiments across disciplines. We begin by discussing some of the advantages of doing experiments on Mechanical Turk, such as easy access to a large, stable, and diverse subject pool, the low cost of doing experiments, and faster iteration between developing theory and executing experiments. While other methods of conducting behavioral research may be comparable to or even better than Mechanical Turk on one or more of the axes outlined above, we will show that when taken as a whole Mechanical Turk can be a useful tool for many researchers. We will discuss how the behavior of workers compares with that of experts and laboratory subjects. Then we will illustrate the mechanics of putting a task on Mechanical Turk, including recruiting subjects, executing the task, and reviewing the work that was submitted. We also provide solutions to common problems that a researcher might face when executing their research on this platform, including techniques for conducting synchronous experiments, methods for ensuring high-quality work, how to keep data private, and how to maintain code security.

Much evidence indicates that emotion enhances memory, but the precise effects of the two primary factors of arousal and valence remain at issue. Moreover, the current knowledge of emotional memory enhancement is based mostly on small samples of extremely emotive stimuli presented in unnaturally high proportions without adequate affective, lexical, and semantic controls. To investigate how emotion affects memory under conditions of natural variation, we tested whether arousal and valence predicted recognition memory for over 2500 words that were not sampled for their emotionality, and we controlled a large variety of lexical and semantic factors. Both negative and positive stimuli were remembered better than neutral stimuli, whether arousing or calming. Arousal failed to predict recognition memory, either independently or interactively with valence. Results support models that posit a facilitative role of valence in memory. This study also highlights the importance of stimulus controls and experimental designs in research on emotional memory.