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

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.

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Abstract

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/).

Item Type:	Conference Proceedings
Series.:	Procedia Computer Science
Publisher:	ELSEVIER SCIENCE BV
Additional Information:	Copy right for this article belongs to the ELSEVIER SCIENCE BV, SARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
Keywords:	Blog document; Data mining; Influential blogger; Online social networks; Profiling; Social blog network
Department/Centre:	Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Date Deposited:	12 May 2016 05:21
Last Modified:	12 May 2016 05:21
URI:	http://eprints.iisc.ac.in/id/eprint/53826

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