PIB: Profiling Influential Blogger in Online Social Networks, A Knowledge Driven Data Mining Approach


Autoria(s): Vasanthakumar, GU; Prajakta, Bagul; Shenoy, Deepa P; Venugopal, KR; Patnaik, LM
Data(s)

2015

Resumo

Online Social Networks (OSNs) facilitate to create and spread information easily and rapidly, influencing others to participate and propagandize. This work proposes a novel method of profiling Influential Blogger (IB) based on the activities performed on one's blog documents who influences various other bloggers in Social Blog Network (SBN). After constructing a social blogging site, a SBN is analyzed with appropriate parameters to get the Influential Blog Power (IBP) of each blogger in the network and demonstrate that profiling IB is adequate and accurate. The proposed Profiling Influential Blogger (PIB) Algorithm survival rate of IB is high and stable. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Formato

application/pdf

Identificador

http://eprints.iisc.ernet.in/53826/1/Pro_Com_Sci_54_362_2015.pdf

Vasanthakumar, GU and Prajakta, Bagul and Shenoy, Deepa P and Venugopal, KR and Patnaik, LM (2015) PIB: Profiling Influential Blogger in Online Social Networks, A Knowledge Driven Data Mining Approach. In: 11th International Conference on Data Mining and Warehousing (ICDMW), AUG 21-23, 2015, Bangalore, INDIA, pp. 362-370.

Publicador

ELSEVIER SCIENCE BV

Relação

http://dx.doi.org/10.1016/j.procs.2015.06.042

http://eprints.iisc.ernet.in/53826/

Palavras-Chave #Electronic Systems Engineering (Formerly, (CEDT) Centre for Electronic Design & Technology)
Tipo

Conference Proceedings

PeerReviewed