Paper Info
Title
A Fuzzy Approach to Social Network Analysis
Abstract
Adjacency relations for social network analysis have usually been tackled in their bidimensional form, in the sense that relations are computed over pairs of objects. Nevertheless, this paper considers the bidimensional case as restrictive and it proposes an approach where the dimension of the analysis is not limited to binary relations. With the aid of fuzzy logic and OWA operators, it is showed that the interpretation of m-ary adjacency relations is the same of binary relations and therefore they can consistently be employed in social network analysis and some novel results be derived. Besides justifying the use of m-ary relations, the paper proposes a way to characterize them and, eventually, it will provide the reader with an example section.
Year
DOI
Venue
2009
10.1109/ASONAM.2009.72
ASONAM
Keywords
Field
DocType
fuzzy logic,fuzzy set theory,social networking (online),OWA operators,fuzzy approach,fuzzy logic,m-ary adjacency relations,social network analysis,OWA operators,Social Network Analysis,adjacency relation,fuzzy sets theory
Adjacency list,Data mining,Computer science,Binary relation,Fuzzy logic,Social network analysis,Fuzzy set,Artificial intelligence,Operator (computer programming),Probability density function,Machine learning
Conference
Citations 
PageRank 
References 
7
0.52
8
Authors
2
Name
Order
Citations
PageRank
Matteo Brunelli130317.62
Michele Fedrizzi234220.01