Leveraging clickthrough data has become a popular approach for evaluating and optimizing information retrieval systems. Although data is plentiful, one must take care when interpreting clicks, since user behavior can be affected by various sources of presentation bias. While the issue of position bias in clickthrough data has been the topic of much study, other presentation bias effects have received comparatively little attention. For instance, since users must decide whether to click on a result based on its summary (e.g., the title, URL and abstract), one might expect clicks to favor "more attractive" results. In this paper, we examine result summary attractiveness as a potential source of presentation bias. This study distinguishes itself from prior work by aiming to detect systematic biases in click behavior due to attractive summaries inflating perceived relevance. Our experiments conducted on the Google web search engine show substantial evidence of presentation bias in clicks towards results with more attractive titles.

We present a logs-based comparison of search patterns across three platforms: computers, iPhones and conventional phones. Our goal is to understand how search users differ from computer-based search users, and we focus heavily on the distribution and variability of tasks that users perform from each platform. The results suggest that search usage is much more focused for the average user than for the average computer-based user. However, search behavior on high-end phones resembles computer-based search behavior more so than search behavior. A wide variety of implications follow from these findings. First, there is no single search interface which is suitable for all phones. We suggest that for the higher-end phones, a close integration with the standard computer-based interface (in terms of personalization and available feature set) would be beneficial for the user, since these phones seem to be treated as an extension of the users' computer. For all other phones, there is a huge opportunity for personalizing the search experience for the user's mobile needs, as these users are likely to repeatedly search for a single type of information need on their phone.