Discovering social photo navigation patterns

Abstract—In general, user browsing behavior has been ex-amined within specific tasks (e.g., search), or in the context of particular web sites or services (e.g., in shopping sites). However, with the growth of social networks and the proliferation of many different types of web services (e.g., news aggregators, blogs, forums, etc.), the web can be viewed as an ecosystem in which a user’s actions in a particular web service may be influenced by the service she arrived from (e.g., are users browsing patterns similar if they arrive at a website via search or via links in aggregators?). In particular, since photos in services like Flickr are used extensively throughout the web, it is common for visitors to the site to arrive via links in many different types of web sites. In this paper, we depart from the hypothesis that visitors to social sites such as Flickr behave differently depending on where they come from. For this purpose, we analyze a large sample of Flickr user logs to discover social photo navigation patterns. More specifically, we classify pages within Flickr into different categories (e.g., “add a friend page”, “single photo page, ” etc.), and by clustering sessions discover important differences in social photo navigation that manifest themselves depending on the type of site users visit before visiting Flickr. Our work examines photo navigation patterns in Flickr for the first time taking into account the referrer domain. Our analysis is useful in that it can contribute to a better understanding of how people use photo services like Flickr, and it can be used to inform the design of user modeling and recommendation algorithms, among others. Index Terms—Social navigation, behavioral modeling, session analysis I