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Mass Media Strategies: Hybrid Approach Using a Bioinspired Algorithm and Social Data Mining
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Author(s): Carlos Alberto Ochoa Ortiz Zezzatti (Juarez City University, México), Darwin Young (COMIMSA Centro Conacyt, México), Camelia Chira (Babes-Bolyai University, Romania), Daniel Azpeitia (Juarez City University, México)and Alán Calvillo (Aguascalientes University, México)
Copyright: 2013
Pages: 26
Source title:
IT Policy and Ethics: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-4666-2919-6.ch015
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Abstract
Evolve computing is a generic name given to the resolution of computational problems with base in models of an evolutionary process. Most of the evolutionary algorithms propose biological paradigms, and concepts of natural selection, mutation, and reproduction. Nevertheless other paradigms exist and can be adopted in the creation of evolutionary algorithms. Many problems involve environments not structured which can be solved from the perspective of cultural paradigms, which offer plenty of category models, where one does which do not know the possible solutions at problem, a common situation in the real life. The intention of this research is analyze the Crowdfunding Model, supporting to a social networking to an Indie Pop Band. Sociological research shows that Crowdfunding tends to reveal a bias toward social similarity. Therefore, in order to model this Project supported with Crowdfunding developing an Agent-Based Model that already manages the social interaction, together with featuring information of MySpace Music evolutionary belief spaces. To introduce these theoretical concepts the authors decided use Cultural Algorithms in our approach, explaining the process in detail.
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