Abstract
The dissertation investigates the correlations and effects between biases in search queries and search query suggestions, search results, and users’ states of knowledge. Search engines are an important factor in opinion formation, while search queries determine the information a user is exposed to in information search. Search query suggestions play a crucial role in what users search for [22]. Biased query suggestions can be especially problematic if a user’s information need is not set and the interaction with query suggestions is likely. Only recently, research has started to investigate the general assumption that biased search queries lead to biased search results, focusing on political stance bias [17]. However, the correlation between biases in search queries and biases in search results has not been sufficiently investigated. Sparse context and limited data access pose challenges in detecting biases in search queries. This dissertation thus contributes datasets and methodological approaches that enable media bias research in the field of search queries and search query suggestions.
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Haak, F. (2023). Investigation of Bias in Web Search Queries. In: Kamps, J., et al. Advances in Information Retrieval. ECIR 2023. Lecture Notes in Computer Science, vol 13982. Springer, Cham. https://doi.org/10.1007/978-3-031-28241-6_50
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