Adjusting Fairness and Diversity in Search Results: User-Driven Re-Ranking for Water Research Literature

Search systems are a crucial means for users to access information. However, considering only the top search results naturally comes with biases that increase even further with personalization, biased databases, or intransparent retrieval systems. We believe that it is essential that users can a) easily understand the characteristics of their search results and b) control them. Our work investigates how the demand for a more fair attribute representation or more diverse perspectives on a topic can be reflected in search results to various degrees. We propose re-ranking methods integrating those user-defined variety settings and an extension of a diversity evaluation metric regarding exposure. Applied to literature search in the multidisciplinary domain of water the methods effectively adjust rankings to match different variety preferences. With that, we demonstrate the potential to enhance user control over search variety, contributing to transparency about entrenched biases and promoting a more user-centered search experience.