Psychometric Analysis and Coupling of Emotions Between State Bulletins and Twitter in India during COVID-19 Infodemic
| Autor: | Baani Leen Kaur Jolly, Palash Aggrawal, Amarjit Singh Sethi, Ponnurangam Kumaraguru, Amogh Gulati, Tavpritesh Sethi |
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| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Psychometrics social media media_common.quotation_subject Lexicon Computer Science - Computers and Society State (polity) Political science Pandemic Computers and Society (cs.CY) Social media Misinformation psychometric analysis government response media_common Social and Information Networks (cs.SI) Government Computer Science - Computation and Language business.industry pandemic Communication Communication. Mass media government COVID-19 Computer Science - Social and Information Networks Public relations P87-96 Causality business Computation and Language (cs.CL) Social Sciences (miscellaneous) |
| Zdroj: | Frontiers in Communication, Vol 6 (2021) |
| DOI: | 10.48550/arxiv.2005.05513 |
| Popis: | COVID-19 infodemic has been spreading faster than the pandemic itself. The misinformation riding upon the infodemic wave poses a major threat to people's health and governance systems. Since social media is the largest source of information, managing the infodemic not only requires mitigating of misinformation but also an early understanding of psychological patterns resulting from it. During the COVID-19 crisis, Twitter alone has seen a sharp 45% increase in the usage of its curated events page, and a 30% increase in its direct messaging usage, since March 6th 2020. In this study, we analyze the psychometric impact and coupling of the COVID-19 infodemic with the official bulletins related to COVID-19 at the national and state level in India. We look at these two sources with a psycho-linguistic lens of emotions and quantified the extent and coupling between the two. We modified path, a deep skip-gram based open-sourced lexicon builder for effective capture of health-related emotions. We were then able to capture the time-evolution of health-related emotions in social media and official bulletins. An analysis of lead-lag relationships between the time series of extracted emotions from official bulletins and social media using Granger's causality showed that state bulletins were leading the social media for some emotions such as Medical Emergency. Further insights that are potentially relevant for the policymaker and the communicators actively engaged in mitigating misinformation are also discussed. Our paper also introduces CoronaIndiaDataset2, the first social media based COVID-19 dataset at national and state levels from India with over 5.6 million national and 2.6 million state-level tweets. Finally, we present our findings as COVibes, an interactive web application capturing psychometric insights captured upon the CoronaIndiaDataset, both at a national and state level. |
| Databáze: | OpenAIRE |
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