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With the rapid spread of information via social media, individuals are prone to misinformation exposure that they may utilize when forming beliefs. Over five experiments (total N = 815 adults, recruited through Amazon Mechanical Turk in the United States), we investigated whether people could ignore quantitative information when they judged for themselves that it was misreported. Participants recruited online viewed sets of values sampled from Gaussian distributions to estimate the underlying means. They attempted to ignore invalid information, which were outlier values inserted into the value sequences. Results indicated participants were able to detect outliers. Nevertheless, participants’ estimates were still biased in the direction of the outlier, even when they were most certain that they detected invalid information. The addition of visual warning cues and different task scenarios did not fully eliminate systematic over- and underestimation. These findings suggest that individuals may incorporate invalid information they meant to ignore when forming beliefs. 

Over the past several decades, researchers in psychology, neuroscience, marketing, and economics have been keen to understand context effects in multialternative, multiattribute decision making. These effects occur when choices among existing alternatives are altered by the addition of a new alternative to the choice set. The effects violate classic decision theories and have led to the development of computational and mathematical models that explain how underlying cognitive and neural mechanisms give rise to the effects. This article reviews dynamic models of these effects, comparing mechanisms across models. Most models of context effects incorporate an attention mechanism, which suggests that attention plays an important role in multialternative, multiattribute decision making. I conclude by discussing recent empirical studies of attention and context effects and hypothesize that changes in attention could be responsible for recently observed reversals in context effects.