Sample NLPDE and NLODE Social-Media Modeling of Information Transmission for Infectious Diseases:Case Study Ebola
| Autor: | Smailhodvic, Armin, Andrew, Keith, Hahn, Lance, Womble, Phillip C., Webb, Cathleen |
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| Rok vydání: | 2015 |
| Předmět: |
Social and Information Networks (cs.SI)
FOS: Computer and information sciences Computer Science - Computers and Society Physics - Physics and Society Computers and Society (cs.CY) FOS: Physical sciences Computer Science - Social and Information Networks Computer Science::Social and Information Networks Physics and Society (physics.soc-ph) Computer Science::Computers and Society |
| DOI: | 10.48550/arxiv.1501.00198 |
| Popis: | We investigate the spreading of information through Twitter messaging related to the spread of Ebola in western Africa using epidemic based dynamic models. Diffusive spreading leads to NLPDE models and fixed point analysis yields systems of NLODE models. When tweets are mapped as connected nodes in a graph and are treated as a time sequenced Markov chain, TSMC, then by the Kurtz theorem these specific paths can be identified as being near solutions to systems of ordinary differential equations that in the large N limit retain many of the features of the original Tweet dynamics. Constraints on the model related to Tweet and re-Tweet rates lead to different versions of the system of equations. We use Ebola Twitter meme based data to investigate a modified four parameter model and apply the resulting fit to an accuracy metric for a set of Ebola memes. In principle the temporal and spatial evolution equations describing the propagation of the Twitter based memes can help ascertain and inform decision makers on the nature of the spreading and containment of an epidemic of this type. Comment: 14 pages, 4 tables, 2 figures |
| Databáze: | OpenAIRE |
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