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Trust and confidence in democratic institutions is at an all-time low. At the same time, many of the complex issues faced by city administrators and politicians remain unresolved. To tackle these concerns, many argue that citizens should,…
Mainstream news organizations shape public perception not only directly through the articles they publish but also through the choices they make about which topics to cover (or ignore) and how to frame the issues they do decide to cover.…
With the arrival of the European Union's General Data Protection Regulation (GDPR), several companies are making significant changes to their systems to achieve compliance. The changes range from modifying privacy policies to redesigning…
One trending application of LLM (large language model) is to use it for content moderation in online platforms. Most current studies on this application have focused on the metric of accuracy -- the extent to which LLMs make correct…
Social media platforms (SMPs) leverage algorithmic filtering (AF) as a means of selecting the content that constitutes a user's feed with the aim of maximizing their rewards. Selectively choosing the contents to be shown on the user's feed…
Content moderators play a key role in keeping the conversation on social media healthy. While the high volume of content they need to judge represents a bottleneck to the moderation pipeline, no studies have explored how models could…
Following the 2016 US presidential election, there has been an increased focus on politically-motivated manipulation of mass-user behavior on social media platforms. Since a large volume of political discussion occurs on these platforms,…
Polarization, declining trust, and wavering support for democratic norms are pressing threats to U.S. democracy. Exposure to verified and quality news may lower individual susceptibility to these threats and make citizens more resilient to…
Social media platforms allow users to create polls to gather public opinion on diverse topics. However, we know little about what such polls are used for and how reliable they are, especially in significant contexts like elections. Focusing…
The data revolution continues to transform every sector of science, industry and government. Due to the incredible impact of data-driven technology on society, we are becoming increasingly aware of the imperative to use data and algorithms…
Despite the common use of rule-based tools for online content moderation, human moderators still spend a lot of time monitoring them to ensure that they work as intended. Based on surveys and interviews with Reddit moderators who use…
Users disclose ever-increasing amounts of personal data on Social Network Service platforms (SNS). Unless SNSs' policies are privacy friendly, this leaves them vulnerable to privacy risks because they ignore the privacy policies. Designers…
User reporting is an essential component of content moderation on many online platforms -- in particular, on end-to-end encrypted (E2EE) messaging platforms where platform operators cannot proactively inspect message contents. However,…
This paper aims to survey various techniques utilized for content moderation in end-to-end encryption systems. We assess the challenging aspect of content moderation: maintaining a safe platform while assuring user privacy. We study the…
Misinformation poses a growing global threat to institutional trust, democratic stability, and public decision-making. While prior research has often portrayed social media as a channel for spreading falsehoods, less is known about the…
Online platforms rely on moderation interventions to curb harmful behavior such hate speech, toxicity, and the spread of mis- and disinformation. Yet research on the effects and possible biases of such interventions faces multiple…
Content moderation is the process of flagging content based on pre-defined platform rules. There has been a growing need for AI moderators to safeguard users as well as protect the mental health of human moderators from traumatic content.…
Personalized recommendation systems often drive users towards more extreme content, exacerbating opinion polarization. While (content-aware) moderation has been proposed to mitigate these effects, such approaches risk curtailing the freedom…
This study explores the relationship between voter trust and their experiences during elections by applying a rule-based data mining technique to the 2022 Survey of the Performance of American Elections (SPAE). Using the Apriori algorithm…
To curb the problem of false information, social media platforms like Twitter started adding warning labels to content discussing debunked narratives, with the goal of providing more context to their audiences. Unfortunately, these labels…