Internet search engines display understanding or misunderstanding of user intent in and through the particular batches of results they retrieve and their perceived relevance. Yet understanding is not simply an automatic outcome but a joint interactional achievement between human and machine. If potential troubles with search queries emerge, either the user or the search engine may initiate repair on the query in ways that resemble repair in human conversation as described in conversation analysis. Users can repair their own queries in first or third position, while search engines can initiate repair from second position. However search-engine interactions currently contain no fourth-position repair. Finally search engines may also complete queries collaboratively with users in ways that are similar to but distinct from repair. In this study we examine interactions between users and search engines using a novel approach we call "computer interaction analysis," which utilizes eye-tracking screen video and a novel notation scheme for transcribing it.

We present findings from a log based study designed to track the adoption of features of a new real-time query refinement interface deployed on the Yahoo search engine. Several trends from the first four months are noted and discussed.

We conducted a series of experiments in which surveyed web search users answered questions about the quality of search results on the basis of the result summaries. Summaries shown to different groups of users were editorially constructed so that they differed in only one attribute, such as length. Some attributes had no effect on users' quality judgments, while in other cases, changing an attribute had a "halo effect" which caused seemingly unrelated dimensions of result quality to be rated higher by users.