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Presenter: Lung-Hao Lee Nov. 3, 2010 @ Room 310
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Introduction Related Work Methods Results ◦ General Gaze Distribution on SERPs ◦ Effects of Task Type ◦ Effects of Ad Quality ◦ Sequence Effects ◦ Blocking Effects Conclusions 2
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Gaze distributions on search engine result pages (SERPs) ◦ “golden triangle” ◦ “F-shaped pattern” The Goal: To understand the visual attention devoted to organic results is influenced by other page elements, e.g. sponsored links, related searches. 3
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Web Search Behavior in general The quality of the results and their presentation ◦ Measure using total time or overall search success (Turpin & Scholer @ SIGIR’06) ◦ Search success is the same for both good and degraded systems (Smith & Kantor @ SIGIR’08) The type of search type ◦ Three general classes of user goals: informational, navigational, and transactional (Border et al. @ SIGIR Forum 2002) ◦ Searchers are more successful for common queries and common goals (Downey et al. @ CIKM’08) Individual differences ◦ Search experts (White & Morris @ SIGIR‘07) and domain experts (White et al. @ WSDM ‘09) are more successful and employ different search strategies than novices 4
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Eye Tracking on SERPs ◦ Searchers examine a SERP is influenced by the position and relevance of the results (Joachims et al. @ SIGIR’05; Pan et al. @ JCMC 2007; Guan & Cutrell @ CHI’07) ◦ Longer snippets lead to better search performance for information tasks (Gutrell & Guan @ CHI’07) ◦ Two different types of searchers: exhaustive and economic (Aula et al. @ INTERACT’05) The Influence of Ads ◦ Sponsored links (10% to 23% of all links) were presented on a SERP (Hochstotter & Lewandowski @ Inf. Sci. 2009) ◦ Integrating ads with the organic results does not increase their click-through rate (Jensen & Spink @ IJIMA 2009) ◦ Behavioral targeting of ads can drastically improve click- through rates (Yan et al. @ WWW’09) 5
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Use eye-tracking as instrument to provide detailed information about the user’s visual attention Gaze tracking can provide data leading to valuable insights about search strategies and processes 6
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Every participant had to solve the same set of 32 search tasks Cached results for each initial query ◦ 24 (75%) of the tasks: a solution within top three results ◦ 6 (19%) of the tasks: a solution can be found in position 4-6 ◦ 2 (6%) of the tasks: a solution was after position 6 7
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SERP Layout 10 results Not containing any special elements like maps, videos, images, or deep links 3 top ads 5 right rail ads Related searches 20 of the 32 initial queries contained related searches 8
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The good ads Select from the ads shown by commercial web search engines such as Bing, Google, and Yahoo The bad ads Select from the same commercial web search engines by generating queries using a subset of the terms occurring in the initial task queries 9
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A trail is one unit of the experiment starting from reading the task description until completing the task The experiment was divided into 4 blocks, of 8 consecutive trails Three types of blocks: Good(G), Bad(B) or Random (R) Each participant was assigned to one of 3 conditions GB (GBGB), BG (BGBG), or RR (RRRR) The order of the tasks in a 32 trails sequences was randomly assigned 10
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Task type (informational / navigational) Quality of the ads (good / bad) shown on the SERPs Block (G/B/R) the trail belongs to Condition (GB/BG/RR) the participant was assigned to 11
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The eye tracker was calibrated using a 5-point calibration After reading the description and the query aloud, the participants pressed a search button to begin searching using the initial query To solve the task, the participants had to navigate to an appropriate web page and point out the solution on it to the experimenters After finding a solution, the participants had to answer the question “How good was the search engine for this task ? ” The experiment took about one hour per participant 12
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17’’ LCD monitor (96dpi) at a screen resolution of 1280*1024 pixels Use the browser IE 7 with a windows size of 1040*996 pixels The page fold was usually between the organic results at position 6 and 7 A Tobii x50 eye tracker which has a tracking frequency of 50 Hz and accuracy of 0.5 o of visual angle Logging of click and gaze data was done by Tobii Studio 13
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38 participants (out of 41) ◦ Age between 26 and 60 years (mean=45.5, delta=8.2) ◦ 21 participants were female and 17 were male 13 unique task sequences 13 participants were assigned to the GB condition, 13 to BG and 12 to RR Valid eye-tracking data for 1210 trails 14
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AOIs (Area of Interest) ◦ Each of the 10 organic results, the top 3 ads, the 5 right rail ads ◦ Each of those result entries contained 3 AOIs matching the title, the summary text snippet and the URL Fixation Impact ◦ Generate a fixation if recorded gaze locations of at least 100ms are close to each other (radius 35 pixels) ◦ Fixation impact fi(A) determine the amount of gaze an AOI A received Clicks ◦ c(A) specifies the number of clicks aggregated for the AOI A e.g. c(top_ads) would be the sum of clicks on any of the 3 top ads Time on SERP ◦ t measures the time the participant spent on the first static SERP for a given task 15
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Gaze on the first SERP represents 88% of the total gaze on all SERPs and 32% of total task time Focus on several aspects of gaze on SERPs ◦ Differences on visual attention (on AOIs) with respect to task type ◦ Differences in visual attention on good and on bad quality ads on SERPs ◦ Sequence effects of presenting good or bad ads in different orders 16
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Most visual attention was devoted to the top few organic results The top ads received as much attention as results around the set fold 17
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There are more clicks that attention on top results Top and right rail ads receive a higher fraction of visual attention than of clicks 18
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Spent significantly more time on SERPs for informational tasks than for navigational ones (mean=16.5s and 12.9s) There was no difference in the distribution of gaze on the top 3 ads Slightly more visual attention during informational tasks for the right rail ads (mean informational=189ms / mean navigational=104ms) Noticeable difference in visual attention on the upper search box which is more than twice as high for information task (1.20 queries) than navigational tasks (1.05 queries) 19
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Spent somewhat less time on SERPs when good quality ads were displayed (mean time 14.2s for good, 15.2s for bad) Top ads of good quality attracted twice as much visual attention as those of bad quality The effect of ad quality was not evident for right rail ads Rate the search engine slightly better when good quality ads were displayed (mean of 4.55 vs. 4.49) The total time to complete a task was about 10% shorter when good quality ads were shown 20
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Good ads generated higher fixation impact than bad ads The quality of the ads had a large effect on click rate The order in which the participants see SERPs with either good or bad ad quality strongly affected their search behavior When SEFPs with good or bad ad quality were presented on random order, participants tended to ignore the ads Predictability is an important factor influencing how users attend to different regions on the SERP 21
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The total time participants needed to complete a task dropped from the first half to the second half of the experiment (1 st half mean=55.7s, 2 nd half mean=40.1s) The time the participants needed to evaluate the first SERP for a given task query decreased from the first to the second half (1 st half mean=15.9s, 2 nd half mean=13.5s) 22
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This research represents a first step in understanding how task, ad quality and sequence influence search interaction ◦ Users’ visual attention towards the top few organic result entries was stronger for informational than for navigational tasks ◦ The quality of ads had a significant influence on the amount of visual attention ◦ Gaze patterns were strongly related to the order in which good and bad ads were presented 23
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Thank you very much Questions & Answers 24
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