While the web offers a great potential to find and share information, the cognitively demanding conditions of online interactions can leave users vulnerable to cognitive biases, such as the confirmation bias-the tendency to favor information that confirms prior attitudes and beliefs when searching for, selecting, interpreting, sharing, and recalling information. This can negatively impact individuals' decision-making and is likely to drive ideological polarization and extremism. With my dissertation, I am investigating whether and how interactive bias mitigation interventions, with a special focus on confirmation bias, could empower web users in making informed, unbiased, and autonomous choices. Based on my findings and observations, I plan to build a framework of user-and context-adaptive bias mitigation approaches during different kinds of web interactions.
|Title of host publication||UMAP2022 - Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization|
|Publisher||Association for Computing Machinery (ACM)|
|Number of pages||5|
|Publication status||Published - 2022|
|Event||30th ACM Conference on User Modeling, Adaptation and Personalization, UMAP2022 - Virtual, Online, Spain|
Duration: 4 Jul 2022 → 7 Jul 2022
|Name||UMAP2022 - Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization|
|Conference||30th ACM Conference on User Modeling, Adaptation and Personalization, UMAP2022|
|Period||4/07/22 → 7/07/22|
Bibliographical noteGreen Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.