---
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: ~
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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
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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: []
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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: ~
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