Use of Hangeul Twitter to Track and Predict Human Influenza Infection
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DOI: 10.1371/journal.pone.0069305
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Cited by:
- Jiangpeng Chen & Xun Lei & Li Zhang & Bin Peng, 2015. "Using Extreme Value Theory Approaches to Forecast the Probability of Outbreak of Highly Pathogenic Influenza in Zhejiang, China," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-10, February.
- Yulin Hswen & Alyssa J. Moran & Siona Prasad & Anna Li & Denise Simon & Lauren Cleveland & Jared B. Hawkins & John S. Brownstein & Jason Block, 2021. "The Federal Menu Labeling Law and Twitter Discussions about Calories in the United States: An Interrupted Time-Series Analysis," IJERPH, MDPI, vol. 18(20), pages 1-11, October.
- Hongxin Xue & Yanping Bai & Hongping Hu & Haijian Liang, 2019. "Regional level influenza study based on Twitter and machine learning method," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-23, April.
- Soo Beom Choi & Insung Ahn, 2020. "Forecasting seasonal influenza-like illness in South Korea after 2 and 30 weeks using Google Trends and influenza data from Argentina," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-14, July.
- Kui Liu & Li Li & Tao Jiang & Bin Chen & Zhenggang Jiang & Zhengting Wang & Yongdi Chen & Jianmin Jiang & Hua Gu, 2016. "Chinese Public Attention to the Outbreak of Ebola in West Africa: Evidence from the Online Big Data Platform," IJERPH, MDPI, vol. 13(8), pages 1-15, August.
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