Abstract: A facility for identifying workers in a crowdsourcing or micro-tasking platform who perform low-quality work and/or are really automated bots is described. To identify users who perform low-quality work and/or are really bots, the facility (1) measures the quality of at least a portion of the work done by each user, and (2) tracks the pattern of behavior performed by each user on the platform—such as which work projects they select, the content of the responses, and the timing of each user interface interaction. The facility uses this information to build and maintain a model, such as a statistical model, that uses the pattern of a user's behavior to predict the level of quality of the user's work. Users for which the model predicts a low level of quality are flagged for manual review, or automatically suspended from working or from receiving payment.

Abstract: A facility for identifying workers in a crowdsourcing or micro-tasking platform who perform low-quality work and/or are really automated bots is described. To identify users who perform low-quality work and/or are really bots, the facility (1) measures the quality of at least a portion of the work done by each user, and (2) tracks the pattern of behavior performed by each user on the platform—such as which work projects they select, the content of the responses, and the timing of each user interface interaction. The facility uses this information to build and maintain a model, such as a statistical model, that uses the pattern of a user's behavior to predict the level of quality of the user's work. Users for which the model predicts a low level of quality are flagged for manual review, or automatically suspended from working or from receiving payment.