Customer misbehavior is a extreme and pervasive hassle in organization–subsidized social media, but previous research offer confined perception into how companies must discover and control it. To cope with this gap, we first broaden a records technology method to discover consumer misbehavior on social media after which devise intervention techniques to discourage it. Specifically, we construct on herbal language processing and deep getting to know strategies to robotically discover consumer misbehavior via way of means of mining clients’ social media sports in collaboration with a main garb organization. The effects display that our algorithmic answer achieves advanced performance, enhancing detection via way of means of 7%–9% in comparison with conventional methods. We then put in force sorts of intervention rules primarily based totally on the point of interest idea of normative behavior that advocates the usage of injunctive norms (i.e., a punishment policy) and descriptive norms (i.e., a not unusualplace identification policy) to restrain consumer misbehavior. We behavior area experiments with the organization to validate those rules. The experimental effects suggest that punishment extensively reduces consumer misbehavior withinside the brief term, however this impact decays over time, while not unusualplace identification has a smaller however greater continual impact on misbehavior reduction. In addition, punishing dysfunctional clients decreases their buy frequency, while enforcing a not unusualplace identification will increase it. Interestingly, our effects display that combining the 2 rules efficaciously alleviates the unfavorable impact of punishment, particularly withinside the lengthy run. We look at the heterogeneous remedy impact on beginner and skilled clients. Finally, a follow-up area test famous that the disclosure of the usage of an synthetic intelligence detector improves the effectiveness of the intervention techniques, and this impact is greater suggested for the punishment and mixture techniques.