Net-TF-SW: Event Popularity Quantification with Network Structure.

KES(2020)

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摘要
Event popularity quantification is essential in the determination of current trends in events on social media and the internet. Particularly, it is important during a crisis to ensure appropriate information transmission and prevention of false-rumor diffusion. Here, we propose Net-TF-SW - a noise-robust and explainable topic popularity analysis method. This method is applied to tweets related to COVID-19 and the Fukushima Daiichi Nuclear Disaster, which are two significant crises that have caused significant anxiety and confusion among Japanese citizens. The proposed method is compared to existing methods, and it is verified to be more robust with respect to noise.
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关键词
COVID-19,Data Mining,Event Popularity,Fukushima Daiichi Nuclear Disaster,Social Media
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