The Impacts of Time Constraint on Users’ Search Strategy at Different Stages
This study examined the effects of time constraints on searchers’ information search strategies during search process, particularly at two search stages (first round and end point). A user experiment with forty participants was conducted, and each participant was asked to search with and without time constraint. The results showed that time constraint had significant effect on users’ first/mean dwell time on search engine result pages (SERPs) during the first query interval; however, time constraint did not influence their dwell time on SERPs or content pages when the whole session was considered, and it only had significant effect on the number of pages viewed per query. The findings indicated that users did employ different search strategies when searching with and without time constraint, and their search strategies changed over time within the search session. Generally, when there was no time constraint, users tended to employ economic-style search strategy at the beginning of search; but when given time constraint, they became more selective and cautious in examining the search results. The findings of this study have implications for search system design to assist searchers under time constraint and help them search more effectively and efficiently.
Using Affective Signals as Implicit Indicators of Information Relevance and Information Processing Strategies
Search engines have become increasingly better at providing information to users. However, they still face major challenges, such as determining how searchers process information, how they make relevance judgments, and how their cognitive or emotional states affect their search progress. We address these challenges by exploring searchers’ affective dimension. In particular, we investigate how feelings, facial expressions, and electrodermal activity (EDA) could help to understand information relevance, search progress, and information processing strategies (IPS). To meet this goal, we designed an experiment in which 45 participants were exposed to affective stimuli prior to solving a fact-finding search task. Results indicate that initial affective dimensions are linked to IPSs, search progress, and task completion. However, further analyses suggest that affective-related features alone have limited utility in the binary classification of relevance using machine learning techniques.
Perception and Effectiveness of Search Advertising on Smartphones
This paper explores the perception and effectiveness of mobile search ads from the perspective of users. The study investigates the attention and interaction of users as well as their subjective estimation of paid listings within Google search results on smartphones. During the tests, each of the 20 users has to accomplish four different search tasks. Data collection methods combine eye-tracking with click-through analysis and interviews. Results indicate that there is no “ad blindness” on mobile search, but similar to desktop search, users also tend to avoid search advertising on smartphones. For mobile search, ads appear to cause higher usability costs than on desktop.