Multi-Perspective Elicitation of Influential Parameters and Measures in Social Network
Sakshi Agarwal1, Shikha Mehta2
1Sakshi Agarwal, Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, India.
2Shikha Mehta, Department of Computer Science & Engineering and Information Technology, Jaypee Institute of Information Technology, Noida, India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 2560-2571 | Volume-8 Issue-8, June 2019 | Retrieval Number: H7075068819/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Recently, there has been enormous curiosity in the phenomenon of influence spread in social and information networks. Researchers from various domains are trying to develop effective and efficient model to estimate social influence. In these models, selection of parameters and measures of the social network for influence estimation is arbitrary. Moreover, these models use different parameters to estimate the influence with respect to same dataset. However, domain specific user’s parameters in influence analysis for social network have not been addressed aptly so far. As, there is no study that precisely focuses on what parameters and measures are suitable for which application, this work presents multi-perspective elicitation of influential parameters and measures in social network. In this paper, we categorized social influence parameters in three classes based on domain specific user’s characteristics i.e., uniform properties of user & their relationship with others time dependent user behaviour and user interaction. Through experiments, we analysed the impact of these three-parameter type in the field of diffusion. Statistics revealed that there are various parameters, which have not yet been explored. Like time dependent user behaviour parameters and user interaction-based parameters have enough scope for research. Therefore, this work intended to open the new road map for researchers and practitioners who aim to develop new technique in this area i.e., social influence.
Keyword: Influence parameters, social influence analysis, social influence measures, social network analysis.
Scope of the Article: Social Networks.