Paper Info
Title
Topic Modeling based on Louvain method in Online Social Networks
Abstract
Online Social Networks (OSNs) are the most used media nowadays, such as Twitter. The OSNs provide valuable information to marketing and competitiveness based on users posts and opinions stored inside huge volume of data from several themes, topics and subjects. In order to mining the topics discussed on an OSN we present a novel application of Louvain method for Topic Modeling based on communities detection in graphs by modularity. The proposed approach succeeded in finding topics in five different datasets composed of textual content from Twitter and Youtube. Another important contribution achieved was about the presence of texts posted by spammers. In this case, a particular behavior observed by graph architecture (density and degree) allows the classification of a topic as natural or artificial, this last created by the spammers on OSNs.
Year
DOI
Venue
2016
abs/10.5555/3021955.3022015
SBSI
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Guilherme Sakaji Kido170.84
Rodrigo Augusto Igawa2112.58
Sylvio Barbon Júnior35014.05