DocumentCode :
187455
Title :
From tweet to graph: Social network analysis for semantic information extraction
Author :
Abascal-Mena, Rocio ; Lema, Rose ; Sedes, Florence
Author_Institution :
Univ. Autonoma Metropolitana - Cuajimalpa, Mexico City, Mexico
fYear :
2014
fDate :
28-30 May 2014
Firstpage :
1
Lastpage :
10
Abstract :
This paper represents a study along the cutting edge of the current analysis of online social network in relation with the contents communicated among users. Twitter data is carefully selected around a fixed hash-tag in order to study the specified content in relation with other contents that users bring to connection. A separate network of hash-tags related (in tweets) is constructed for different days; the networks are analyzed within advanced Gephi package, providing several measures -degree, betweenness centrality, communities, as well as the longest path, by which the evolution of communication around specified concepts is quantified. Our study is absolutely in the current trend of analysis of online social networks that, going beyond mere topology, reveals relevant linguistic and social categories and their dynamics.
Keywords :
information analysis; information retrieval; social networking (online); Gephi package; betweenness centrality measure; communities measure; degree measure; hash-tag network; linguistic category; semantic information extraction; social category; social network analysis; Bridges; Communities; Context; Pragmatics; Semantics; Twitter; Social Network Analysis; Social Web; Theory of Graphs; Twitter; community detection; text mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Research Challenges in Information Science (RCIS), 2014 IEEE Eighth International Conference on
Conference_Location :
Marrakech
Type :
conf
DOI :
10.1109/RCIS.2014.6861047
Filename :
6861047
Link To Document :
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