Related papers: Challenges in Restructuring Community-based Modera…
With peak content moderation seemingly behind us, this paper revisits its punitive side. But instead of focusing on who is being (disproportionately) moderated, it focuses on the punishment itself and explores the question of how content…
Extensive efforts in automated approaches for content moderation have been focused on developing models to identify toxic, offensive, and hateful content with the aim of lightening the load for moderators. Yet, it remains uncertain whether…
Rules are a critical component of the functioning of nearly every online community, yet it is challenging for community moderators to make data-driven decisions about what rules to set for their communities. The connection between a…
Social media platforms curate access to information and opportunities, and so play a critical role in shaping public discourse today. The opaque nature of the algorithms these platforms use to curate content raises societal questions. Prior…
Moderation of reader comments is a significant problem for online news platforms. Here, we experiment with models for automatic moderation, using a dataset of comments from a popular Croatian newspaper. Our analysis shows that while…
Social media platforms like Facebook and Reddit host thousands of user-governed online communities. These platforms sanction communities that frequently violate platform policies; however, public perceptions of such sanctions remain…
This study presents the first large-scale quantitative analysis of the efficiency of X's Community Notes, a crowdsourced moderation system for identifying and contextualising potentially misleading content. Drawing on over 1.8 million…
Data generated by audits of social media websites have formed the basis of our understanding of the biases presented in algorithmic content recommendation systems. As legislators around the world are beginning to consider regulating the…
Social media platforms utilize Machine Learning (ML) and Artificial Intelligence (AI) powered recommendation algorithms to maximize user engagement, which can result in inadvertent exposure to harmful content. Current moderation efforts,…
Corrections given by ordinary social media users, also referred to as Social Correction have emerged as a viable intervention against misinformation as per the recent literature. However, little is known about how often users give disputing…
One potential disadvantage of social tagging systems is that due to the lack of a centralized vocabulary, a crowd of users may never manage to reach a consensus on the description of resources (e.g., books, users or songs) on the Web. Yet,…
In many online communities, community leaders (i.e., moderators and administrators) can proactively filter undesired content by requiring posts to be approved before publication. But although many communities adopt post approvals, there has…
Wikipedia -- like most peer production communities -- suffers from a basic problem: the amount of work that needs to be done (articles to be created and improved) exceeds the available resources (editor effort). Recommender systems have…
Conversational moderation of online communities is crucial to maintaining civility for a constructive environment, but it is challenging to scale and harmful to moderators. The inclusion of sophisticated natural language generation modules…
Polarization is a troubling phenomenon that can lead to societal divisions and hurt the democratic process. It is therefore important to develop methods to reduce it. We propose an algorithmic solution to the problem of reducing…
The last 30 years have seen the creation of a variety of electronic collaboration tools for science and business. Some of the best-known collaboration tools support text editing (e.g., wikis). Wikipedia's success shows that large-scale…
Our paper investigates the use of discourse embedding techniques to develop a community recommendation system that focuses on mental health support groups on social media. Social media platforms provide a means for users to anonymously…
We present Moderator, a policy-based model management system that allows administrators to specify fine-grained content moderation policies and modify the weights of a text-to-image (TTI) model to make it significantly more challenging for…
As an alternative to Twitter and other centralized social networks, the Fediverse is growing in popularity. The recent, and polemical, takeover of Twitter by Elon Musk has exacerbated this trend. The Fediverse includes a growing number of…
Social media platforms are constantly shifting towards algorithmically curated content based on implicit or explicit user feedback. Regulators, as well as researchers, are calling for systematic social media algorithmic audits as this shift…