相关论文: A User-Driven Framework for Regulating and Auditin…

Flagging mechanisms on social media platforms allow users to report inappropriate posts/accounts for review by content moderators. These reports are pivotal to platforms' efforts toward regulating norm violations. This paper examines how…

Whenever a social media user decides to share a story, she is typically pleased to receive likes, comments, shares, or, more generally, feedback from her followers. As a result, she may feel compelled to use the feedback she receives to…

We consider the task of linking social media accounts that belong to the same author in an automated fashion on the basis of the content and metadata of their corresponding document streams. We focus on learning an embedding that maps…

On social media algorithms for content promotion, accounting for users preferences, might limit the exposure to unsolicited contents. In this work, we study how the same contents (videos) are consumed on different platforms -- i.e. Facebook…

Social networks have triumphed in communicating people online, but they have also been exploited to launch influence operations for manipulating society. The deployment of software-controlled accounts (e.g., social bots) has proven to be…

An increasing number of regulations propose AI audits as a mechanism for achieving transparency and accountability for artificial intelligence (AI) systems. Despite some converging norms around various forms of AI auditing, auditing for the…

Online social media platforms use automated moderation systems to remove or reduce the visibility of rule-breaking content. While previous work has documented the importance of manual content moderation, the effects of automated content…

How can online communities execute a focused vision for their space? Curation offers one approach, where community leaders manually select content to share with the community. Curation enables leaders to shape a space that matches their…

Social media platforms moderate content for each user by incorporating the outputs of both platform-wide content moderation systems and, in some cases, user-configured personal moderation preferences. However, it is unclear (1) how end…

Social media platforms continue to struggle with the growing presence of social bots-automated accounts that can influence public opinion and facilitate the spread of disinformation. Over time, these social bots have advanced significantly,…

In this paper, we demonstrate how the state-of-the-art machine learning and text mining techniques can be used to build effective social media-based substance use detection systems. Since a substance use ground truth is difficult to obtain…

We argue that governments should mandate a three-tier anonymity framework on social-media platforms as a reactionary measure prompted by the ease-of-production of deepfakes and large-language-model-driven misinformation. The tiers are…

The idea that social media platforms like Twitter are inhabited by vast numbers of social bots has become widely accepted in recent years. Social bots are assumed to be automated social media accounts operated by malicious actors with the…

Modern social media platforms, such as TikTok, Facebook, and YouTube, rely on recommendation systems to personalize content for users based on user interactions with endless streams of content, such as "For You" pages. However, these…

Researchers and journalists have repeatedly shown that algorithms commonly used in domains such as credit, employment, healthcare, or criminal justice can have discriminatory effects. Some organizations have tried to mitigate these effects…

Recommender systems can be found everywhere today, shaping our everyday experience whenever we're consuming content, ordering food, buying groceries online, or even just reading the news. Let's imagine we're in the process of building a…

User-generated content (UGC) on social media platforms is vulnerable to incitements and manipulations, necessitating effective regulations. To address these challenges, those platforms often deploy automated content moderators tasked with…

Recommender systems often rely on models which are trained to maximize accuracy in predicting user preferences. When the systems are deployed, these models determine the availability of content and information to different users. The gap…

We tackle the challenge of topic classification of tweets in the context of analyzing a large collection of curated streams by news outlets and other organizations to deliver relevant content to users. Our approach is novel in applying…

Facebook uses Artificial Intelligence for targeting users with advertisements based on the events in which they engage like sharing, liking, making comments, posts by a friend, a group creation, etcetera. Each user interacts with these…