An empirical study of interest, task complexity, and search behaviour on user engagement

作者：

Highlights：

• User engagement (UE) is an important outcome measure in interactive information retrieval.

• We asked 144 Amazon Mechanical Turk participants to complete 6 search tasks on different topics.

• We used questionnaires and log analysis to investigate the effects of task interest and complexity on UE.

• Effort (greater perceived task difficulty, higher SERP exploration) had a negative effect on UE.

• Success (greater task determinability, more bookmarked pages) was positively associated with UE.

摘要

•User engagement (UE) is an important outcome measure in interactive information retrieval.•We asked 144 Amazon Mechanical Turk participants to complete 6 search tasks on different topics.•We used questionnaires and log analysis to investigate the effects of task interest and complexity on UE.•Effort (greater perceived task difficulty, higher SERP exploration) had a negative effect on UE.•Success (greater task determinability, more bookmarked pages) was positively associated with UE.

论文关键词：Interactive information retrieval,Search tasks,Task complexity,User engagement,Online search behaviours,Multilevel modelling,00-01,99-00

论文评审过程：Received 9 April 2019, Revised 3 December 2019, Accepted 11 February 2020, Available online 21 February 2020, Version of Record 21 February 2020.

论文官网地址：https://doi.org/10.1016/j.ipm.2020.102226