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

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          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.

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          Most cited references18

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          The Dynamics of Public Attention: Agenda-Setting Theory Meets Big Data

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            Agenda-setting Effects of Business News on the Public's Images and Opinions about Major Corporations

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              Using text mining and sentiment analysis for online forums hotspot detection and forecast

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                Author and article information

                Contributors
                amartya3@gmail.com
                sunanda.bose@msn.com
                Journal
                J Comput Soc Sci
                J Comput Soc Sci
                Journal of Computational Social Science
                Springer Singapore (Singapore )
                2432-2717
                2432-2725
                21 October 2020
                : 1-34
                Affiliations
                GRID grid.216499.1, ISNI 0000 0001 0722 3459, Department of Computer Science and Engineering, , Jadavpur University, ; Kolkata, India
                Author information
                http://orcid.org/0000-0001-6789-5740
                https://orcid.org/0000-0002-6484-9682
                Article
                88
                10.1007/s42001-020-00088-3
                7576103
                33102926
                05bd2a6b-0316-4435-a0f0-f993297612b9
                © Springer Nature Singapore Pte Ltd. 2020

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 9 July 2020
                : 3 October 2020
                Categories
                Research Article

                covid-19,news sentiment analysis,unsupervised opinion mining,news negativity,correlation,news agenda

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