Around the world in 60 days: an exploratory study of impact of COVID-19 on online global news sentiment

Amartya Chakraborty () and Sunanda Bose ()
Additional contact information
Amartya Chakraborty: Jadavpur University
Sunanda Bose: Jadavpur University

Journal of Computational Social Science, 2020, vol. 3, issue 2, No 5, 367-400

Abstract: Abstract The world is going through an unprecedented crisis due to COVID-19 breakout, and people all over the world are forced to stay indoors for safety. In such a situation, the rise and fall of the number of affected cases or deaths has turned into a constant headline in most news channels. Consequently, there is a lack of positivity in the world-wide news published in different forms of media. Texts based on news articles, movie reviews, tweets, etc. are often analyzed by researchers, and mined for determining opinion or sentiment, using supervised and unsupervised methods. The proposed work takes up the challenge of mining a comprehensive set of online news texts, for determining the prevailing sentiment in the context of the ongoing pandemic, along with a statistical analysis of the relation between actual effect of COVID-19 and online news sentiment. The amount and observed delay of impact of the ground truth situation on online news is determined on a global scale, as well as at country level. The authors conclude that at a global level, the news sentiment has a good amount of dependence on the number of new cases or deaths, while the effect varies for different countries, and is also dependent on regional socio-political factors.

Keywords: COVID-19; News sentiment analysis; Unsupervised opinion mining; News negativity; Correlation; News agenda (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://link.springer.com/10.1007/s42001-020-00088-3 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:jcsosc:v:3:y:2020:i:2:d:10.1007_s42001-020-00088-3

Ordering information: This journal article can be ordered from
http://www.springer. ... iences/journal/42001

DOI: 10.1007/s42001-020-00088-3

Access Statistics for this article

Journal of Computational Social Science is currently edited by Takashi Kamihigashi

More articles in Journal of Computational Social Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().