Net-TF-SW: Event Popularity Quantification with Network Structure | Zendy

Hiroshi Nagaya | Zendy; Teruaki Hayashi | Zendy; Yukio Ohsawa | Zendy; Fujio Toriumi | Zendy; Hiroyuki Torii | Zendy; Kazuko Uno | Zendy

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

Author(s) -

Hiroshi Nagaya,

Teruaki Hayashi,

Yukio Ohsawa,

Fujio Toriumi,

Hiroyuki Torii,

Kazuko Uno

Publication year - 2020

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2020.09.194

Subject(s) - popularity , computer science , rumor , confusion , noise (video) , the internet , event (particle physics) , social media , covid-19 , transmission (telecommunications) , computer security , data mining , data science , artificial intelligence , telecommunications , world wide web , political science , medicine , psychology , public relations , physics , disease , pathology , quantum mechanics , psychoanalysis , infectious disease (medical specialty) , law , image (mathematics)

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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