Published on in Vol 4, No 4 (2018): Oct-Dec
Journals
- Nagaya H, Hayashi T, A. Torii H, Ohsawa Y. Topic Jerk Detector: Detection of Tweet Bursts Related to the Fukushima Daiichi Nuclear Disaster. Information 2020;11(7):368 View
- Hasegawa S, Suzuki T, Yagahara A, Kanda R, Aono T, Yajima K, Ogasawara K. Changing Emotions About Fukushima Related to the Fukushima Nuclear Power Station Accident—How Rumors Determined People’s Attitudes: Social Media Sentiment Analysis. Journal of Medical Internet Research 2020;22(9):e18662 View
- de Melo T, Figueiredo C. Comparing News Articles and Tweets About COVID-19 in Brazil: Sentiment Analysis and Topic Modeling Approach. JMIR Public Health and Surveillance 2021;7(2):e24585 View
- Fujii S, Kunii Y, Nonaka S, Hamaie Y, Hino M, Egawa S, Kuriyama S, Tomita H. Real-Time Prediction of Medical Demand and Mental Health Status in Ukraine under Russian Invasion Using Tweet Analysis. The Tohoku Journal of Experimental Medicine 2023;259(3):177 View
- Zarrabeitia-Bilbao E, Jaca-Madariaga M, Rio-Belver R, Álvarez-Meaza I. Nuclear energy: Twitter data mining for social listening analysis. Social Network Analysis and Mining 2023;13(1) View
- GÖKMEN E. A Study on the Appearance of the Kahramanmaraş Earthquake on Social Media. OPUS Toplum Araştırmaları Dergisi 2023;20(55):576 View
- Kobayashi T, Yamada K, Murakami M, Ozaki A, Torii H, Uno K. Assessment of attitudes toward critical actors during public health crises. International Journal of Disaster Risk Reduction 2024;108:104559 View