Abstract
AbstractConventional review websites display a list of item search results with average rating scores (i.e., star ratings). We propose a method of designing snippets that encourage users to search items on review websites more carefully. The proposed snippets include aspect indicators that identify negative aspects if the item has a good star rating and vice versa. We expect the aspect indicators will help mitigate biases due to ranking position and star ratings by making users feel a “loss” if they do not carefully examine items. Our user study showed that the proposed method of including aspect indicators for loss aversion made participants spend more time searching a list of search results and checking items with worse star ratings, especially when searching hospitals. In contrast, showing aspect indicators that conformed to star ratings caused shortsighted review searches.KeywordsInformation retrievalCognitive biasHuman factorSearch user interaction
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