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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| Vydáno v: | Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 s. 1175 - 1182 |
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| Hlavní autoři: | , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
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New York, NY, USA
ACM
31.07.2017
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| Edice: | ACM Conferences |
| Témata: |
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
Theory of computation
> Design and analysis of algorithms
> Graph algorithms analysis
> Network flows
Theory of computation
> Theory and algorithms for application domains
> Algorithmic game theory and mechanism design
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| ISBN: | 1450349935, 9781450349932 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Lee, Eva K. Wang, Zixing |
| Author_xml | – sequence: 1 givenname: Eva K. surname: Lee fullname: Lee, Eva K. email: eva.lee@gatech.edu organization: Center for Operations Research in Medicine and Healthcare, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, U.S.A – sequence: 2 givenname: Zixing surname: Wang fullname: Wang, Zixing email: zwang411@gatech.edu organization: Center for Operations Research in Medicine and Healthcare, School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, U.S.A |
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| Copyright | 2017 Owner/Author |
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| DOI | 10.1145/3110025.3125430 |
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| Editor | Diesner, Jana Ferrari, Elena Xu, Guandong |
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| Keywords | HIV/AIDS influence calibration influence optimization Sociology-based influence network |
| Language | English |
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| PublicationTitle | Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017 ASONAM 2017 : proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining : Sydney, Australia, 31 July-03 August, 2017 |
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| Snippet | Strong social networks can encourage healthy behaviors. In this paper, we introduce a sociology-based computational framework for influence networks. The model... |
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| SubjectTerms | 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 |
| Subtitle | Application to Clergy Influence in HIV/AIDS Outreach |
| Title | A Computational Framework for Influence Networks |
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