A Computational Framework for Influence Networks Application to Clergy Influence in HIV/AIDS Outreach

Strong social networks can encourage healthy behaviors. In this paper, we introduce a sociology-based computational framework for influence networks. The model construct is generic and is applicable to diverse social network analysis. We demonstrate its usage in calibrating the positive influence of...

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Bibliographic Details
Published in:Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 pp. 1175 - 1182
Main Authors: Lee, Eva K., Wang, Zixing
Format: Conference Proceeding
Language:English
Published: New York, NY, USA ACM 31.07.2017
Series:ACM Conferences
Subjects:
Applied computing
Applied computing > Law, social and behavioral sciences
Applied computing > Law, social and behavioral sciences > Sociology
Human-centered computing
Human-centered computing > Collaborative and social computing
Human-centered computing > Collaborative and social computing > Collaborative and social computing design and evaluation methods
Human-centered computing > Collaborative and social computing > Collaborative and social computing design and evaluation methods > Social network analysis
Information systems
Information systems > Information systems applications
Mathematics of computing
Mathematics of computing > Discrete mathematics
Mathematics of computing > Discrete mathematics > Graph theory
Mathematics of computing > Discrete mathematics > Graph theory > Network flows
Networks
Networks > Network types
Networks > Network types > Overlay and other logical network structures
Networks > Network types > Overlay and other logical network structures > Online social networks
Theory of computation
Theory of computation > Design and analysis of algorithms
Theory of computation > Design and analysis of algorithms > Graph algorithms analysis
Theory of computation > Design and analysis of algorithms > Graph algorithms analysis > Network flows
Theory of computation > Theory and algorithms for application domains
Theory of computation > Theory and algorithms for application domains > Algorithmic game theory and mechanism design
Theory of computation > Theory and algorithms for application domains > Algorithmic game theory and mechanism design > Social networks
HIV/AIDS
influence calibration
influence optimization
Sociology-based influence network
ISBN:1450349935, 9781450349932
Online Access:Get full text
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Summary:Strong social networks can encourage healthy behaviors. In this paper, we introduce a sociology-based computational framework for influence networks. The model construct is generic and is applicable to diverse social network analysis. We demonstrate its usage in calibrating the positive influence of church clergy in spreading HIV/AIDs information in a large metropolitan city. Five experiments are designed to contrast influence with respect to the interaction style between clergy and churchgoers. Competitive and non-competitive knowledge dissemination are also analyzed. The results show that when only one set of information exists, the spreading scope is directly proportional to the product of population size and the disease infection rate. When competing information is present, the importance of clergy in spreading the information decreases when the original propagation sources are ample. However, if sufficient interaction and trust are present among the clergy and the participants, the clergy's positive influence remains significant despite pre-existing knowledge. The generalized framework requires minimal regional data to establish the influence network. It provides useful policy insights for decision makers to determine effective avenues for information dissemination through community influencers.
ISBN:1450349935
9781450349932
DOI:10.1145/3110025.3125430