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M.S. Pera

147 records found

Kid Query

Co-designing an Application to Scaffold Query Formulation

In this work, we discuss the findings emerging from co-design sessions between children ages 6 to 11 and adults, which were conducted to advance knowledge on how to best support children using well-known search tools for online information discovery. Specifically, we argue that b ...
Popularity bias is a prominent phenomenon in recommender systems (RS), especially in the music domain. Although popularity bias mitigation techniques are known to enhance the fairness of RS while maintaining their high performance, there is a lack of understanding regarding users ...
When using web search engines to conduct inquiries on debated topics, searchers' interactions with search results are commonly affected by a combination of searcher and system biases. While prior work has mainly investigated these biases in isolation, there is a lack of a compreh ...
Web search has evolved into a platform people rely on for opinion formation on debated topics. Yet, pursuing this search intent can carry serious consequences for individuals and society and involves a high risk of biases. We argue that web search can and should empower users to ...
Information Retrieval (IR) remains an active, fast-paced area of research. However, most advances in IR have predominantly benefited the so-called “classical” users, e.g., English-speaking adults. We envision IR4U2as a forum to spotlight efforts that, while sparse, consider diver ...
We discuss the foundation of a collaborative effort to explore AI's role in supporting (teachers and) children in their learning experiences. We integrate principles of educational psychology, AI, and HCI, and align with best practices in education while undertaking a human-cente ...

Misinformation in video recommendations

An exploration of Top-N recommendation algorithms

With this paper, we delve into the problem of misinformation propagation in the video recommendation domain, focusing on top-N recommendation algorithms (RAs). We evaluate a broad spectrum of RAs to probe their ability to minimize misinformation recommendations while optimizing t ...

AltRecSys

A Workshop on Alternative, Unexpected, and Critical Work on Recommendation

The AltRecsys workshop, held in conjunction with the 18th edition of the ACM Conference on Recommender Systems (RecSys) in Bari, Italy, provides a platform for highlighting “alternative” work in recommender systems. Modeled after alt.chi and the CRAFT sessions at the FAccT confer ...
Large Language Models (LLMs) are expected to significantly impact various socio-technical systems, offering transformative possibilities for improved interaction between humans and technology. However, their integration poses complex challenges due to the intricate interplay betw ...

Not Just Algorithms

Strategically Addressing Consumer Impacts in Information Retrieval

Information Retrieval (IR) systems have a wide range of impacts on consumers. We offer maps to help identify goals IR systems could—or should—strive for, and guide the process of scoping how to gauge a wide range of consumer-side impacts and the possible interventions needed to a ...
Current approaches in automatic readability assessment have found success with the use of large language models and transformer architectures. These techniques lead to accuracy improvement, but they do not offer the interpretability that is uniquely required by the audience most ...
Children often interact with search engines within a classroom context to complete assignments or discover new information. To successfully identify relevant resources among those presented on a search engine results page (SERP), users must first be able to comprehend the text in ...
In this work, we reason how focusing on Information Retrieval (IR) for children and involving them in participatory studies would benefit the IR community. The Child Computer Interaction (CCI) community has embraced the child as a protagonist as their main philosophy, regarding c ...

From Potential to Practice

Intellectual Humility During Search on Debated Topics

An essential characteristic for unbiased and diligent information-seeking that can enable informed opinion formation and decision-making is intellectual humility (IH), the awareness of the limitations of one's knowledge and opinions. While researchers have recognized the potentia ...

Into the Unknown

Exploration of Search Engines' Responses to Users with Depression and Anxiety

Researchers worldwide have explored the behavioral nuances that emerge from interactions of individuals afflicted by mental health disorders (MHD) with persuasive technologies, mainly social media. Yet, there is a gap in the analysis pertaining to a persuasive technology that is ...

"Who are you?"

Identifying Young Users from a Single Search Query

As an initial step towards enabling the adaptation of (popular, and widely used) web search environments so that they can better serve children and ease their path towards information discovery, we introduce Recognizing Young Searchers (RYSe). RYSe leverages lexical, syntactical, ...
This forum provides a space to engage with the challenges of designing for intelligent algorithmic experiences. We invite articles that tackle the tensions between research and practice when integrating AI and UX design. We welcome interdisciplinary debate, artful critique, forwa ...
Social networks are a platform for individuals and organizations to connect with each other and inform, advertise, spread ideas, and ultimately influence opinions. These platforms have been known to propel misinformation. We argue that this could be compounded by the recommender ...

Where a Little Change Makes a Big Difference

A Preliminary Exploration of Children’s Queries

This paper contributes to the discussion initiated in a recent SIGIR paper describing a gap in the information retrieval (IR) literature on query understanding–where they come from and whether they serve their purpose. Particularly the connection between query variability and sea ...