People are susceptible to an array of cognitive biases, which can result in systematic errors
and deviations from rational decision making. Over the past decade, an increasing amount …

Understanding how people interact with search interfaces is core to the field of Interactive
Information Retrieval (IIR). While various models have been proposed (eg, Belkin's ASK …

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 …

This paper investigates the significant impact different prompts have on the behaviour of
ChatGPT when used for health information seeking. As people more and more depend on …

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 …

Societal biases can influence Information Retrieval system results, and conversely, search
results can potentially reinforce existing societal biases. Recent research has therefore …

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 …

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 …

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 (eg, the …

We introduce and quantify a relatively new form of influence: the Answer Bot Effect (ABE). In
a 2015 report in PNAS, researchers demonstrated the power that biased search results have …