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Millions of online communities are governed by volunteer moderators, who shape their communities by setting and enforcing rules, recruiting additional moderators, and participating in the community themselves. These moderators must…
Current content moderation follows a reactive, trial-and-error approach, where interventions are applied and their effects are only measured post-hoc. In contrast, we introduce a proactive, predictive approach that enables moderators to…
Effective content moderation in online communities is often a delicate balance between maintaining content quality and fostering user participation. In this paper, we introduce post guidance, a novel approach to community moderation that…
Increasingly people form opinions based on information they consume on online social media. As a result, it is crucial to understand what type of content attracts people's attention on social media and drive discussions. In this paper we…
Online community moderators are on the front lines of combating problems like hate speech and harassment, but new modes of interaction can introduce unexpected challenges. In this paper, we consider moderation practices and challenges in…
Social media platforms have been establishing content moderation guidelines and employing various moderation policies to counter hate speech and misinformation. The goal of this paper is to study these community guidelines and moderation…
Content moderation practices and technologies need to change over time as requirements and community expectations shift. However, attempts to restructure existing moderation practices can be difficult, especially for platforms that rely on…
Sensitive attributes are legally protected characteristics that should not be used to discriminate. Careful steps have been taken to minimize the risk of human bias regarding these fields, such as race and age. Large language models (LLMs)…
When toxic online communities on mainstream platforms face moderation measures, such as bans, they may migrate to other platforms with laxer policies or set up their own dedicated websites. Previous work suggests that within mainstream…
Toxicity detection algorithms, originally designed with reactive content moderation in mind, are increasingly being deployed into proactive end-user interventions to moderate content. Through a socio-technical lens and focusing on contexts…
Growing amount of comments make online discussions difficult to moderate by human moderators only. Antisocial behavior is a common occurrence that often discourages other users from participating in discussion. We propose a neural network…
The rise of online platforms has enabled covert illicit activities, including online prostitution, to pose challenges for detection and regulation. In this study, we introduce REDDIX-NET, a novel benchmark dataset specifically designed for…
Developing a strong community requires empowered leadership capable of overcoming governance challenges. New online platforms have given users opportunities to practice governance through content moderation roles. The over 2.8 million…
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…
Social media users may perceive moderation decisions by the platform differently, which can lead to frustration and dropout. This study investigates users' perceived justice and fairness of online moderation decisions when they are exposed…
As the use of social platforms continues to evolve, in areas such as cyber-security and defence, it has become imperative to develop adaptive methods for tracking, identifying and investigating cyber-related activities on these platforms.…
Toxic language, such as hate speech, can deter users from participating in online communities and enjoying popular platforms. Previous approaches to detecting toxic language and norm violations have been primarily concerned with…
We present a holistic approach to building a robust and useful natural language classification system for real-world content moderation. The success of such a system relies on a chain of carefully designed and executed steps, including the…
Advice forums are a crowdsourced way to reinforce cultural norms and moral behavior. Sites like Reddit contain massive amounts of natural language human interaction, with rules and norms unique to each individual subreddit community. To…
Online platforms and communities establish their own norms that govern what behavior is acceptable within the community. Substantial effort in NLP has focused on identifying unacceptable behaviors and, recently, on forecasting them before…