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 ...

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, ...

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 ...

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 ...

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. ...

Featured snippets that attempt to satisfy users’ information needs directly on top of the first search engine results page (SERP) have been shown to strongly impact users’ post-search attitudes and beliefs. In the context of debated but scientifically ...

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 ...

Due to the increasing amount of information shared online every day, the need for sound and reliable ways of distinguishing between trustworthy and non-trustworthy information is as present as ever. One technique for performing fact-checking at scale is ...

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 ...

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' ...

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 ...

Web search increasingly provides a platform for users to seek advice on important personal decisions but may be biased in several different ways. One result of such biases is the search engine manipulation effect (SEME): when a list of search results ...

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 ...

We are living in an era of global digital platforms, eco-systems of algorithmic processes that serve users worldwide. However, the increasing exposure to diversity online – of information and users – has led to important considerations of bias. A given ...

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 ...

Systems aiming to aid consumers in their decision-making (e.g., by implementing persuasive techniques) are more likely to be effective when consumers trust them. However, recent research has demonstrated that the machine learning algorithms that ...