| Autor: |
Anubha Bhaik, Pradeep Kumar Gupta, Mohammad Khubeb Siddiqui, Ruben Morales-Menendez |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Revista Argentina de Ciencias del Comportamiento. 14:37-48 |
| ISSN: |
1852-4206 |
| DOI: |
10.32348/1852.4206.v14.n2.30816 |
| Popis: |
The outbreak of the COVID – 19 pandemic has caused a notable challenge to the well-being of people all around the globe. In such times, it is of foremost importance to analyze the information posted by people on social media. In this study, a Twitter-based dataset related to COVID-19 has been analyzed, and the effect of the pandemic on societal behavior has been revealed. Tweets have been hydrated and pre-processed using the NLTK toolkit to find the most frequently posted COVID- related words. This research can help identify the social response of people to the Pandemic, realizing what people are majorly concerned about and extracting knowledge about the daily trend of sentiments around the world. It has been concluded from our analysis that rather than the expected negative trend in the use of COVID-19 terms on a daily basis, more positive figurative language has been used in the posted tweets. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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