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Analysis of US Covid-19 Twitter Data Social Interest and Topic Changes
17th International Computer Engineering Conference, ICENCO 2021 ; : 14-17, 2021.
Article in English | Scopus | ID: covidwho-1759075
ABSTRACT
In this research, we analyzed the Covid-19 phenomena in the USA through analysis of Twitter data related to the Covid-19 pandemic in USA. We made this analysis with Twitter data from April and May of the year 2020. What we did differently in this research was focusing on one hashtag only so that we could focus on a fixed community. Our goal is to see if there is a connection or a pattern that could be found between the different output measures and plots. To do this, we focused on the country of the USA as a use-case. The difference in this analysis is that we didn't create our dataset by downloading data generally related to Covid-19 in the USA (from multiple tags), but rather we tracked one Twitter hashtag, ensuring that we track a certain group of the population so we could be sure about our population interest calculation results. © 2021 IEEE.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 17th International Computer Engineering Conference, ICENCO 2021 Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: 17th International Computer Engineering Conference, ICENCO 2021 Year: 2021 Document Type: Article