Collaboration and reputation in social web search

Recent research has highlighted the inherently collaborative nature of many Web search tasks, even though collaborative
searching is not supported by mainstream search engines. In this paper, we examine the activity of early adopters of HeyStaks, a collaborative Web search framework that is designed to complement mainstream search engines such as Google, Bing, and Yahoo. The utility allows users to search as normal, using their favourite search engine, while benefiting from a more collaborative and social search experience. HeyStaks supports searchers by harnessing the experiences
of others, in order to enhance organic mainstream result-lists. We review some early evaluation results that speak
to the practical benefits of search collaboration in the context of the recently proposed Reader-to-Leader social media
analysis framework [11]. In addition, we explore the idea of utilising the reputation model introduced by McNally et al.[6] in order to identify the search leaders in HeyStaks, i.e. those users who are responsible for driving collaboration in
the HeyStaks application.