Heterogeneous Latent Topic Discovery for Semantic Text Mining

Author(s):  
Yawen Li ◽  
Di Jiang ◽  
Rongzhong Lian ◽  
Xueyang Wu ◽  
Conghui Tan ◽  
...  
Author(s):  
Hamoon Jafarian ◽  
Mahin Mohammadi ◽  
Alireza Javaheri ◽  
Makram Sukarieh ◽  
Mohsen Yoosefi Nejad ◽  
...  

Background: Social networks are a good source for monitoring public health during the outbreak of COVID-19, these networks play an important role in identifying useful information. Objectives: This study aims to draw a comparison of the public’s reaction in Twitter among the countries of West Asia (a.k.a Middle East) and North Africa in order to make an understanding of their response regarding the same global threat. Methods: 766,630 tweets in four languages (Arabic, English French, and Farsi) tweeted in March 2020, were investigated. Results: The results indicate that the only common theme among all languages is “government responsibilities (political)” which indicates the importance of this subject for all nations. Conclusion: Although nations react similarly in some aspects, they respond differently in others and therefore, policy localization is a vital step in confronting problems such as COVID-19 pandemic.


2007 ◽  
Vol 43 (3) ◽  
pp. 752-768 ◽  
Author(s):  
Aurora Pons-Porrata ◽  
Rafael Berlanga-Llavori ◽  
José Ruiz-Shulcloper
Keyword(s):  

2013 ◽  
Author(s):  
Ronald N. Kostoff ◽  
◽  
Henry A. Buchtel ◽  
John Andrews ◽  
Kirstin M. Pfiel

2020 ◽  
Vol 42 (5) ◽  
pp. 279-307
Author(s):  
Yonglim Joe
Keyword(s):  

2019 ◽  
Vol 19 (2) ◽  
pp. 29-38
Author(s):  
Young-Hee Kim ◽  
◽  
Taek-Hyun Lee ◽  
Jong-Myoung Kim ◽  
Won-Hyung Park ◽  
...  

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