A study of user interactions with “Query AutoCompletion” and “Related Searches” on the Google search engine

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

Purpose: The Query AutoCompletion and Related Search capabilities are auxiliary tools in the query formulation phase. This study is an attempt to analyze how users interact with Query AutoCompletion and RS on Google. Methods: In this study, a within-subjects experimental design has been utilized. Using the purposive sampling method, 30 graduate students were selected to perform the search tasks on Google. Research data were collected using a researcher-made questionnaire consisting of demographic characteristics and seven search tasks. The search tasks were searched by the participants on the Google. In total, 297 questions were presented in 210 search sessions, and the users’ interactive behavior in using Query AutoCompletion and the statistical Related Search was recorded by Camtasia Studio screen recorder software. Results: Findings showed that the users used the Query AutoCompletion and the Related Search in 44.78% of the queries, while in search tasks, users used Query AutoCompletion (35.5%) more than Related Search (9.43%), and the difference was statistically significant ( p -value = 0.000). According to the research findings, the level of complexity of search tasks also affected the use of Query AutoCompletion, Related Search, and Query AutoCompletion + Related Search. As the number of session queries increased, the use of Query AutoCompletion and Related Search increased significantly. In addition, the users tended to use Query AutoCompletion at the top of the search list (the first rank = 60%). Conclusion: The results of this study can provide valuable insights into how users interact with Query AutoCompletion and Related Search and can also be used to design these mechanisms in information retrieval tools.