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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…
User interface (UI) personalization can improve usability and user experience. However, current systems offer limited opportunities for customization, and third-party solutions often require significant effort and technical skills beyond…
Digital platforms such as social media and e-commerce websites adopt Recommender Systems to provide value to the user. However, the social consequences deriving from their adoption are still unclear. Many scholars argue that recommenders…
Personalized recommendations form an important part of today's internet ecosystem, helping artists and creators to reach interested users, and helping users to discover new and engaging content. However, many users today are skeptical of…
Social media platforms have rapidly adopted algorithmic curation with little consideration for the potential harm to users' mental well-being. We present findings from design workshops with 21 participants diagnosed with mental illness…
News recommendation and personalization is not a solved problem. People are growing concerned of their data being collected in excess in the name of personalization and the usage of it for purposes other than the ones they would think…
As algorithms increasingly shape user experiences on personalized recommendation platforms, there is a growing need for tools that empower end users to audit these algorithms for potential bias and harms. This paper introduces a novel…
In micro-blogging platforms, people connect and interact with others. However, due to cognitive biases, they tend to interact with like-minded people and read agreeable information only. Many efforts to make people connect with those who…
Social media platforms are often criticized for fostering antisocial behavior rather than prosocial behavior. Yet, testing interventions to encourage prosocial dispositions, such as open-mindedness, has been hindered by researchers' limited…
Personalization is pervasive in the online space as, when combined with learning, it leads to higher efficiency and revenue by allowing the most relevant content to be served to each user. However, recent studies suggest that such…
Facebook News Feed personalization algorithm has a significant impact, on a daily basis, on the lifestyle, mood and opinion of millions of Internet users. Nonetheless, the behavior of such algorithms usually lacks transparency, motivating…
The pitfalls of centralized social networks, such as Facebook and Twitter/X, have led to concerns about control, transparency, and accountability. Decentralized social networks have emerged as a result with the goal of empowering users.…
The recent growth of digital interventions for mental well-being prompts a call-to-arms to explore the delivery of personalised recommendations from a user's perspective. In a randomised placebo study with a two-way factorial design, we…
Personalization has traditionally depended on platform-specific user models that are optimized for prediction but remain largely inaccessible to the people they describe. As LLM-based assistants increasingly mediate search, shopping,…
People who use social media are learning about how the companies that run these platforms make their decisions on who gets to see what through visual indicators in the interface (UI) of each social media site. These indicators are different…
Recommender systems shape online interactions by matching users with creators content to maximize engagement. Creators, in turn, adapt their content to align with users preferences and enhance their popularity. At the same time, users…
The term filter bubble has been coined to describe the situation of online users which---due to filtering algorithms---live in a personalised information universe biased towards their own interests.In this paper we use an agent-based…
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…
Bluesky is a nascent Twitter-like and decentralized social media network with novel features and unprecedented data access. This paper provides a characterization of its interaction network, studying the political leaning, polarization,…
Modern web-based platforms show ranked lists of recommendations to users, attempting to maximise user satisfaction or business metrics. Typically, the goal of such systems boils down to maximising the exposure probability for items that are…