McNally, KevinKevinMcNallyO'Mahony, Michael P.Michael P.O'MahonySmyth, BarryBarrySmythCoyle, MauriceMauriceCoyleBriggs, PeterPeterBriggs2010-10-182010-10-182010-09http://hdl.handle.net/10197/25222nd Workshop on Recommender Systems and the Social Web, in association with The 4th ACM Conference on Recommender Systems (RecSys 2010), Barcelona, Spain, September 26-30, 2010 2010Recent 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.472404 bytesapplication/pdfenCollaborative web search,HeyStaksReputation modelSocial recommender systemInternet searching--SoftwareWeb co-browsing--SoftwareOnline social networksRecommender systems (Information filtering)Conference Publicationhttps://creativecommons.org/licenses/by-nc-sa/1.0/