Your browser doesn't support javascript.
Topics, Sentiments, and Emotions Triggered by COVID-19-Related Tweets from IRAN and Turkey Official News Agencies.
Ahmad, Waseem; Wang, Bang; Xu, Han; Xu, Minghua; Zeng, Zeng.
  • Ahmad W; School of Electronic Information and Communications, Huazhong University of Science and Technology (HUST), Wuhan, China.
  • Wang B; School of Electronic Information and Communications, Huazhong University of Science and Technology (HUST), Wuhan, China.
  • Xu H; School of Journalism and Information Communication, Huazhong University of Science and Technology (HUST), Wuhan, China.
  • Xu M; School of Journalism and Information Communication, Huazhong University of Science and Technology (HUST), Wuhan, China.
  • Zeng Z; Institute for Infocomm Research, Agency for Science, Technology and Research (ASTAR), Singapore, Singapore.
SN Comput Sci ; 2(5): 394, 2021.
Article in English | MEDLINE | ID: covidwho-1682764
ABSTRACT
There is no doubt that the COVID-19 epidemic posed the most significant challenge to all governments globally since January 2020. People have to readapt after the epidemic to daily life with the absence of an effective vaccine for a long time. The epidemic has led to society division and uncertainty. With such issues, governments have to take efficient procedures to fight the epidemic. In this paper, we analyze and discuss two official news agencies' tweets of Iran and Turkey by using sentiment- and semantic analysis-based unsupervised learning approaches. The main topics, sentiments, and emotions that accompanied the agencies' tweets are identified and compared. The results are analyzed from the perspective of psychology, sociology, and communication.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Topics: Vaccines Language: English Journal: SN Comput Sci Year: 2021 Document Type: Article Affiliation country: S42979-021-00789-0

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Topics: Vaccines Language: English Journal: SN Comput Sci Year: 2021 Document Type: Article Affiliation country: S42979-021-00789-0