Paper Info
Title
A New Content-Based Model for Social Network Analysis
Abstract
This paper presents a novel model for social network analysis in which, rather than analyzing the quantity of relationships (co-authorships, business relations, friendship, etc.), we analyze their communicative content. Text mining and clustering techniques are used to capture the content of communication and to identify the most popular themes. The social analyst is then able to perform a study of the network evolution in terms of the relevant themes of collaboration, the detection of new concepts gaining popularity, and the existence of popular themes that could benefit from better cooperation.The methodology is experimented in the domain of a Network of Excellence on enterprise interoperability, INTEROP.
Year
DOI
Venue
2008
10.1109/ICSC.2008.30
ICSC
Keywords
Field
DocType
statistical analysis,clustering algorithms,text mining,feature extraction,social sciences,ontologies,social network analysis,social network,taxonomy,data mining
Ontology (information science),Data science,Enterprise interoperability,Friendship,Computer science,Popularity,Social network analysis,Cluster analysis,Excellence,Business relations
Conference
Citations 
PageRank 
References 
21
1.15
15
Authors
4
Name
Order
Citations
PageRank
paola velardi11553163.66
Roberto Navigli219713.50
Alessandro Cucchiarelli322636.38
Fulvio D'antonio47812.08