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--- abstract: "Online social networks are rapidly asserting themselves as popular services on the Web. A central point is\r\nto determine whether two distinct users can be considered similar, a crucial concept with interesting consequences on the possibility to accomplish targeted actions like, for example, political and social aggregations or commercial promotions. In this chapter we propose an approach in order to estimate the similarity\r\nof two users based on the knowledge of social ties (i.e., common friends and groups of users)\r\nexisting among users, and the analysis of activities (i.e., social events) in which users are involved. For\r\neach of these indicators, we draw a local measure of user similarity which takes into account only their\r\njoint behaviours. After this, we consider the whole network of relationships among users along with local\r\nvalues of similarities and combine them to obtain a global measure of similarity. Such a computation is\r\ncarried out by applying the Katz coefficient, a popular parameter introduced in Social Science research.\r\nFinally, similarity values produced for each social activity are merged into a unique value of similarity by\r\napplying linear regression." altloc: [] chapter: ~ commentary: ~ commref: ~ confdates: ~ conference: ~ confloc: ~ contact_email: ~ creators_id: [] creators_name: - family: De Meo given: Pasquale honourific: '' lineage: '' - family: Ferrara given: Emilio honourific: '' lineage: '' - family: Fiumara given: Giacomo honourific: '' lineage: '' date: 2011 date_type: published datestamp: 2011-10-01 00:34:22 department: ~ dir: disk0/00/00/76/34 edit_lock_since: ~ edit_lock_until: 0 edit_lock_user: ~ editors_id: [] editors_name: [] eprint_status: archive eprintid: 7634 fileinfo: application/pdf;http://cogprints.org/7634/1/Finding_similar_users%2DCR.pdf full_text_status: public importid: ~ institution: ~ isbn: ~ ispublished: pub issn: ~ item_issues_comment: [] item_issues_count: ~ item_issues_description: [] item_issues_id: [] item_issues_reported_by: [] item_issues_resolved_by: [] item_issues_status: [] item_issues_timestamp: [] item_issues_type: [] keywords: ~ lastmod: 2011-10-01 00:34:22 latitude: ~ longitude: ~ metadata_visibility: show note: 'ISBN: 978-1-61350-444-4' number: ~ pagerange: ~ pubdom: TRUE publication: 'Social Networking and Community Behavior Modeling: Qualitative and Quantitative Measurement' publisher: Igi Publishing refereed: TRUE referencetext: ~ relation_type: [] relation_uri: [] reportno: ~ rev_number: 9 series: ~ source: ~ status_changed: 2011-10-01 00:34:22 subjects: - comp-sci-mach-dynam-sys succeeds: ~ suggestions: ~ sword_depositor: ~ sword_slug: ~ thesistype: ~ title: Finding Similar Users in Facebook type: bookchapter userid: 14714 volume: ~