Modeling Searcher Frustration
نویسندگان
چکیده
When search engine users have trouble finding what they are looking for, they become frustrated. In a pilot study, we found that 36% of queries submitted end with users being moderately to extremely frustrated. By modeling searcher frustration, search engines can predict the current state of user frustration, tailor the search experience to help the user find what they are looking for, and avert them from switching to another search engine. Among other observations, we found that across the fifteen users and six tasks in our study, frustration follows a law of conservation: a frustrated user tends to stay frustrated and a non-frustrated user tends to stay not frustrated. Future work includes extracting features from the query log data and readings from three physical sensors collected during the study to predict searcher frustration.
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