Searched for: author%253A%2522Tintarev%252C%2520N.%2522
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Rieger, A. (author), Draws, T.A. (author), Theune, Mariët (author), Tintarev, N. (author)
When people use web search engines to find information on debated topics, the search results they encounter can influence opinion formation and practical decision-making with potentially far-reaching consequences for the individual and society. However, current web search engines lack support for information-seeking strategies that enable...
journal article 2024
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Draws, T.A. (author), Natesan Ramamurthy, Karthikeyan (author), Baldini, Ioana (author), Dhurandhar, Amit (author), Padhi, Inkit (author), Timmermans, Benjamin (author), Tintarev, N. (author)
One way to help users navigate debated topics online is to apply stance detection in web search. Automatically identifying whether search results are against, neutral, or in favor could facilitate diversification efforts and support interventions that aim to mitigate cognitive biases. To be truly useful in this context, however, stance...
conference paper 2023
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Barile, Francesco (author), Draws, T.A. (author), Inel, Oana (author), Rieger, A. (author), Najafian, S. (author), Ebrahimi Fard, Amir (author), Hada, Rishav (author), Tintarev, N. (author)
Social choice aggregation strategies have been proposed as an explainable way to generate recommendations to groups of users. However, it is not trivial to determine the best strategy to apply for a specific group. Previous work highlighted that the performance of a group recommender system is affected by the internal diversity of the group...
journal article 2023
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Draws, T.A. (author), Roy, N. (author), Inel, Oana (author), Rieger, A. (author), Hada, Rishav (author), Yalcin, Mehmet Orcun (author), Timmermans, Benjamin (author), Tintarev, N. (author)
Adverse phenomena such as the search engine manipulation effect (SEME), where web search users change their attitude on a topic following whatever most highly-ranked search results promote, represent crucial challenges for research and industry. However, the current lack of automatic methods to comprehensively measure or increase viewpoint...
conference paper 2023
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Rieger, A. (author), Bredius, F. (author), Tintarev, N. (author), Pera, M.S. (author)
We often use search engines when seeking information for opinion-forming and decision-making on debated topics. However, searching for resources on debated topics to gain well-rounded knowledge is cognitively demanding, leaving us vulnerable to cognitive biases, such as confirmation bias. This can impede well-informed decision-making, and on...
conference paper 2023
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Yurrita Semperena, M. (author), Draws, T.A. (author), Balayn, A.M.A. (author), Murray-Rust, D.S. (author), Tintarev, N. (author), Bozzon, A. (author)
Recent research claims that information cues and system attributes of algorithmic decision-making processes affect decision subjects' fairness perceptions. However, little is still known about how these factors interact. This paper presents a user study (N = 267) investigating the individual and combined effects of explanations, human...
conference paper 2023
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Draws, T.A. (author), Inel, O. (author), Tintarev, N. (author), Baden, Christian (author), Timmermans, Benjamin (author)
Research in the area of human information interaction (HII) typically represents viewpoints on debated topics in a binary fashion, as either against or in favor of a given topic (e.g., the feminist movement). This simple taxonomy, however, greatly reduces the latent richness of viewpoints and thereby limits the potential of research and...
conference paper 2022
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Rieger, A. (author), Shaheen, Qurat Ul Ain (author), Sierra, Carles (author), Theune, Mariet (author), Tintarev, N. (author)
Online debates allow for large-scale participation by users with different opinions, values, and backgrounds. While this is beneficial for democratic discourse, such debates often tend to be cognitively demanding due to the high quantity and low quality of non-expert contributions. High cognitive demand, in turn, can make users vulnerable to...
conference paper 2022
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Najafian, S. (author), Delic, Amra (author), Tkalcic, Marko (author), Tintarev, N. (author)
Explanations can help users to better understand why items have been recommended. Additionally, explanations for group recommender systems need to consider further goals than single-user recommender systems. For example, we need to balance group members' need for privacy with their need for transparency, since a transparent explanation might...
conference paper 2021
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Draws, T.A. (author), Rieger, A. (author), Inel, O. (author), Gadiraju, Ujwal (author), Tintarev, N. (author)
Recent research has demonstrated that cognitive biases such as the confirmation bias or the anchoring effect can negatively affect the quality of crowdsourced data. In practice, however, such biases go unnoticed unless specifically assessed or controlled for. Task requesters need to ensure that task workflow and design choices do not trigger...
conference paper 2021
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Musto, Cataldo (author), Tintarev, N. (author), Inel, O. (author), Polignano, Marco (author), Semeraro, Giovanni (author), Ziegler, Jürgen (author)
Adaptive and personalized systems have become pervasive technologies that are gradually playing an increasingly important role in our daily lives. Indeed, we are now used to interact every day with algorithms that help us in several scenarios, ranging from services that suggest us music to be listened to or movies to be watched, to personal...
conference paper 2021
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Draws, T.A. (author), Tintarev, N. (author), Gadiraju, Ujwal (author), Bozzon, A. (author), Timmermans, B. (author)
In web search on debated topics, algorithmic and cognitive biases strongly influence how users consume and process information. Recent research has shown that this can lead to a search engine manipulation effect (SEME): when search result rankings are biased towards a particular viewpoint, users tend to adopt this favored viewpoint. To better...
conference paper 2021
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Mulder, M. (author), Inel, O. (author), Oosterman, J.E.G. (author), Tintarev, N. (author)
Diversity in personalized news recommender systems is often defined as dissimilarity, and operationalized based on topic diversity (e.g., corona versus farmers strike). Diversity in news media, however, is understood as multiperspectivity (e.g., different opinions on corona measures), and arguably a key responsibility of the press in a...
conference paper 2021
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Draws, T.A. (author), Tintarev, N. (author), Gadiraju, Ujwal (author), Bozzon, A. (author), Timmermans, Benjamin (author)
The way pages are ranked in search results influences whether the users of search engines are exposed to more homogeneous, or rather to more diverse viewpoints. However, this viewpoint diversity is not trivial to assess. In this paper we use existing and novel ranking fairness metrics to evaluate viewpoint diversity in search result rankings. We...
conference paper 2021
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Rieger, A. (author), Theune, Mariët (author), Tintarev, N. (author)
Cognitive biases in the context of consuming online information filtered by recommender systems may lead to sub-optimal choices. One approach to mitigate such biases is through interface and interaction design. This survey reviews studies focused on cognitive bias mitigation of recommender system users during two processes: 1) item selection and...
conference paper 2021
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Inel, O. (author), Duricic, Tomislav (author), Kaur, Harmanpreet (author), Lex, Elisabeth (author), Tintarev, N. (author)
Online videos have become a prevalent means for people to acquire information. Videos, however, are often polarized, misleading, or contain topics on which people have different, contradictory views. In this work, we introduce natural language explanations to stimulate more deliberate reasoning about videos and raise users’ awareness of...
journal article 2021
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Rieger, A. (author), Draws, T.A. (author), Theune, Mariët (author), Tintarev, N. (author)
During online information search, users tend to select search results that confirm previous beliefs and ignore competing possibilities. This systematic pattern in human behavior is known as confirmation bias. In this paper, we study the effect of obfuscation (i.e., hiding the result unless the user clicks on it) with warning labels and the...
conference paper 2021
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Najafian, S. (author), Draws, T.A. (author), Barile, Francesco (author), Tkalcic, Marko (author), Yang, J. (author), Tintarev, N. (author)
Recent research has shown that explanations serve as an important means to increase transparency in group recommendations while also increasing users' privacy concerns. However, it is currently unclear what personal and contextual factors affect users' privacy concerns about various types of personal information. This paper studies the effect...
conference paper 2021
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Alonso, Jose M. (author), Barro, Senén (author), Bugarín, Alberto (author), van Deemter, Kees (author), Gardent, Claire (author), Gatt, Albert (author), Reiter, Ehud (author), Sierra, Carles (author), Theune, Mariët (author), Tintarev, N. (author), Yano, Hitoshi (author), Budzynska, Katarzyna (author)
We have defined an interdisciplinary program for training a new generation of researchers who will be ready to leverage the use of Artificial Intelligence (AI)-based models and techniques even by non-expert users. The final goal is to make AI self-explaining and thus contribute to translating knowledge into products and services for economic...
conference paper 2021
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Draws, T.A. (author), Liu, Jody (author), Tintarev, N. (author)
Support or opposition concerning a debated claim such as abortion should be legal can have different underlying reasons, which we call perspectives. This paper explores how opinion mining can be enhanced with joint topic modeling, to identify distinct perspectives within the topic, providing an informative overview from unstructured text. We...
conference paper 2021
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