Title
Towards better measurement of attention and satisfaction in mobile search
Abstract
Web Search has seen two big changes recently: rapid growth in mobile search traffic, and an increasing trend towards providing answer-like results for relatively simple information needs (e.g., [weather today]). Such results display the answer or relevant information on the search page itself without requiring a user to click. While clicks on organic search results have been used extensively to infer result relevance and search satisfaction, clicks on answer-like results are often rare (or meaningless), making it challenging to evaluate answer quality. Together, these call for better measurement and understanding of search satisfaction on mobile devices. In this paper, we studied whether tracking the browser viewport (visible portion of a web page) on mobile phones could enable accurate measurement of user attention at scale, and provide good measurement of search satisfaction in the absence of clicks. Focusing on answer-like results in web search, we designed a lab study to systematically vary answer presence and relevance (to the user's information need), obtained satisfaction ratings from users, and simultaneously recorded eye gaze and viewport data as users performed search tasks. Using this ground truth, we identified increased scrolling past answer and increased time below answer as clear, measurable signals of user dissatisfaction with answers. While the viewport may contain three to four results at any given time, we found strong correlations between gaze duration and viewport duration on a per result basis, and that the average user attention is focused on the top half of the phone screen, suggesting that we may be able to scalably and reliably identify which specific result the user is looking at, from viewport data alone.
Year
DOI
Venue
2014
10.1145/2600428.2609631
SIGIR
Keywords
Field
DocType
search on mobile phone,search process,user attention and satisfaction,viewport logging
Mobile search,Organic search,Information needs,Viewport,Web page,Information retrieval,Computer science,Eye tracking,Scrolling,Computer user satisfaction
Conference
Citations 
PageRank 
References 
59
1.38
20
Authors
4
Name
Order
Citations
PageRank
Dmitry Lagun135114.96
Chih-Hung Hsieh2591.38
Dale Webster3591.38
Vidhya Navalpakkam443519.77