We study behavioral changes in twitter users as a result of interacting with automated bots. Based on the list of malicious bots identified and shut down by Twitter in the wake of 2016 US presidential election, we are able to identify about 54 thousand human twitter users who have interacted with one such bot. We first establish the baseline behavioral pattern of users in the period before interaction and then measure behavioral changes observed around the period of interaction. Using a quasi-experimental research design, we document economically and statistically significant quantitative and qualitative changes in users’ behavior.

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