A New Content-Based Model for Social Network Analysis

Author

Velardi, Paola ; Navigli, Roberto ; Cucchiarelli, Alessandro ; Antonio, Fulvio D.

Author_Institution

Univ. of Roma La Sapienza, Rome

fYear

2008

fDate

4-7 Aug. 2008

Firstpage

18

Lastpage

25

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.

Keywords

pattern clustering; social sciences; statistical analysis; INTEROP; clustering techniques; collaboration relevant themes; communicative content; content-based model; enterprise interoperability; social network analysis; text mining; semantic social networks; topic clustering;

fLanguage

English

Publisher

ieee

Conference_Titel

Semantic Computing, 2008 IEEE International Conference on

Conference_Location

Santa Clara, CA

Print_ISBN

978-0-7695-3279-0

Electronic_ISBN

978-0-7695-3279-0

Type

conf

DOI

10.1109/ICSC.2008.30

Filename

4597169