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What can we learn about the Middle East Respiratory Syndrome (MERS) outbreak from tweets?

1 Columbia University Medical Center, NY, USA
2 Department of Mathematics, CA, UCLA, USA
3 Library, UCLA, CA, USA
4 Department of Nursing, Hoseo University, Asan, South Korea

Middle East Respiratory Syndrome (MERS, 메르스 in Korean) is an emerging deadly viral respiratory disease with no treatment. This study applied a triangulation approach of quantitative structure and content miningtechniques while incorporating qualitative approaches guided by domain experts, to understand #MERS and #메르스 tweets. This study sought to gain insights about culturally-appropriate nursing activities for an emerging global acute disease management.
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Citation: Sunmoo Yoon, Da Kuang, Peter Broadwell, Haeyoung Lee, Michelle Odlum. What can we learn about the Middle East Respiratory Syndrome (MERS) outbreak from tweets?. Big Data and Information Analytics, 2017, 2(3&4): 203-207. doi: 10.3934/bdia.2017013

References

  • 1. Fawcett J, Ellenbecker CH. A proposed conceptual model of nursing and population health. Nurs Outlook 2015;63:288-98.
  • 2. Dodds PS, Harris KD, Kloumann IM, Bliss CA, Danforth CM. Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter. PloS one 2011;6:e26752.
  • 3. Lui M, Baldwin T. Cross-domain feature selection for language identification. In Proceedings of 5th International Joint Conference on Natural Language Processing; 2011: Citeseer.
  • 4. Blei DM, Ng AY, Jordan MI. Latent dirichlet allocation. Journal of machine Learning research 2003;3:993-1022.
  • 5. Kuang D, Park H. Fast rank-2 nonnegative matrix factorization for hierarchical document clustering. Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining; 2013: ACM. p. 739-47.
  • 6. Yoon S, Bakken S. Methods of knowledge discovery in tweets. NI 2012: Proceedings of the 11th International Congress on Nursing Informatics; 2012: American Medical Informatics Association.

 

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Copyright Info: 2017, Sunmoo Yoon, et al., licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

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