DocumentCode :
3155702
Title :
"How Well Do We Know Each Other?" Detecting Tie Strength in Multidimensional Social Networks
Author :
Pappalardo, Luca ; Rossetti, Giulio ; Pedreschi, Dino
Author_Institution :
KDD Lab., Univ. of Pisa, Pisa, Italy
fYear :
2012
fDate :
26-29 Aug. 2012
Firstpage :
1040
Lastpage :
1045
Abstract :
The advent of social media have allowed us to build massive networks of weak ties: acquaintances and nonintimate ties we use all the time to spread information and thoughts. Conversely, strong ties are the people we really trust, people whose social circles tightly overlap with our own and, often, they are also the people most like us. Unfortunately, the majority of social media do not incorporate explicitly tie strength information in the creation and management of relationships, and treat all users the same: friend or stranger, with little or nothing in between. In the current work, we address the challenging issue of detecting on online social networks the strong and intimate ties from the huge mass of such mere social contacts. In order to do so, we propose a novel multidimensional definition of tie strength which exploits the existence of multiple online social links between two individuals. We test our definition on a multidimensional network constructed over users in Foursquare, Twitter and Facebook, analyzing the structural role of strong and weak links, and the correlations with the most common similarity measures.
Keywords :
social networking (online); social sciences computing; Facebook; Foursquare; Twitter; acquaintances ties; information spreading; multidimensional social networks; multidimensional tie strength definition; multiple online social links; nonintimate ties; online social networks; similarity measures; social circles; social contacts; social media; social networking sites; thought spreading; tie strength detection; weak ties; Bridges; Communities; Facebook; Media; Organizations; Twitter; Link Mining; Multidimensional Social Networks; Tie Strength;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-2497-7
Type :
conf
DOI :
10.1109/ASONAM.2012.180
Filename :
6425622
Link To Document :
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