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

Nagaya, Hiroshi; Hayashi, Teruaki; Ohsawa, Yukio; Toriumi, Fujio; Torii, Hiroyuki A; Uno, Kazuko

Nagaya, Hiroshi; Hayashi, Teruaki; Ohsawa, Yukio; Toriumi, Fujio; Torii, Hiroyuki A; Uno, Kazuko.

Afiliación

Nagaya H; School of Engineering, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo, 113-8656, Japan.
Hayashi T; School of Engineering, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo, 113-8656, Japan.
Ohsawa Y; School of Engineering, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo, 113-8656, Japan.
Toriumi F; School of Engineering, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo, 113-8656, Japan.
Torii HA; School of Science, The University of Tokyo, 7-3-1 Hongo Bunkyo-ku, Tokyo, 113-0033, Japan.
Uno K; Louis Pasteur Center for Medical Research, 103-5, Tanaka Monzen-cho, Sakyo-ku, Kyoto City, Kyoto, 606-8225, Japan.

Procedia Comput Sci ; 176: 1693-1702, 2020.

Article en En | MEDLINE | ID: mdl-33042302

Palabras clave

COVID-19; Data Mining; Event Popularity; Fukushima Daiichi Nuclear Disaster; Social Media

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Procedia Comput Sci Año: 2020 Tipo del documento: Article País de afiliación: Japón Pais de publicación: Países Bajos

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