Perception and Understanding of Social Annotations in Web Search

In Proc. of WWW2013, International World Wide Web Conferences Steering Committee, pp. 403-412


As web search increasingly becomes reliant on social signals, it is imperative for us to understand the effect of these signals on users' behavior. There are multiple ways in which social signals can be used in search: (a) to surface and rank important social content; (b) to signal to users which results are more trustworthy and important by placing annotations on search results. We focus on the latter problem of understanding how social annotations affect user behavior. In previous work, through eyetracking research we learned that users do not generally seem to fixate on social annotations when they are placed at the bottom of the search result block, with 11% probability of fixation [22]. A second eyetracking study showed that placing the annotation on top of the snippet block might mitigate this issue [22], but this study was conducted using mock-ups and with expert searchers. In this paper, we describe a study conducted with a new eyetracking mix-method using a live traffic search engine with the suggested design changes on real users using the same experimental procedures. The study comprised of 11 subjects with an average of 18 tasks per subject using an eyetrace-assisted retrospective think-aloud protocol. Using a funnel analysis, we found that users are indeed more likely to notice the annotations with a 60% probability of fixation (if the annotation was in view). Moreover, we found no learning effects across search sessions but found significant differences in query types, with subjects having a lower chance of fixating on annotations for queries in the news category. In the interview portion of the study, users reported interesting "wow" moments as well as usefulness in recalling or re-finding content previously shared by oneself or friends. The results not only shed light on how social annotations should be designed in search engines, but also how users make use of social annotations to make decisions about which pages are useful and potentially trustworthy.