Quantifying Feature Importance for Online Content Moderation
This work addresses the need for user-centered moderation strategies by identifying key predictive features, though it is incremental in applying existing quantification methods to a new dataset.
The study tackled the problem of predicting user behavioral changes after moderation interventions on Reddit by analyzing 753 features, finding that a small set of features consistently predicted changes in activity, toxicity, and diversity, with performance varying by task.
Accurately estimating how users respond to moderation interventions is paramount for developing effective and user-centred moderation strategies. However, this requires a clear understanding of which user characteristics are associated with different behavioural responses, which is the goal of this work. We investigate the informativeness of 753 socio-behavioural, linguistic, relational, and psychological features, in predicting the behavioural changes of 16.8K users affected by a major moderation intervention on Reddit. To reach this goal, we frame the problem in terms of "quantification", a task well-suited to estimating shifts in aggregate user behaviour. We then apply a greedy feature selection strategy with the double goal of (i) identifying the features that are most predictive of changes in user activity, toxicity, and participation diversity, and (ii) estimating their importance. Our results allow identifying a small set of features that are consistently informative across all tasks, and determining that many others are either task-specific or of limited utility altogether. We also find that predictive performance varies according to the task, with changes in activity and toxicity being easier to estimate than changes in diversity. Overall, our results pave the way for the development of accurate systems that predict user reactions to moderation interventions. Furthermore, our findings highlight the complexity of post-moderation user behaviour, and indicate that effective moderation should be tailored not only to user traits but also to the specific objective of the intervention.