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- W4323024791 endingPage "199" @default.
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- W4323024791 abstract "This chapter is dedicated to the application of the grey relational analysis in the public opinion mining. Due to the complex economic and social situation the entire mankind has passed in the last few years since the occurrence of the COVID-19 pandemics, the chapter features an application on the public opinion assessment in connection with the COVID-19 vaccination process. The incidence of COVID-19 vaccination news on the people’s opinion regarding vaccination has been analyzed during two periods of time, featuring two major events related to COVID-19 vaccination, namely the first announcement that an effective vaccine is available and the start of the vaccination campaign. A series of tweets have been extracted using specific COVID-19 and vaccination keywords. Classical machine learning and deep learning algorithms have been tested in terms of accuracy, precision, recall and f-score in order to determine the best performing stance classifier. Based on the evolution of the number of tweets in the three categories during the two periods, a grey relational analysis has been conducted and it has been determined that for both periods, there is a powerful relationship between the number of tweets containing news related to the COVID-19 vaccination and the number of tweets containing in favor or against messages regarding COVID-19 vaccination." @default.
- W4323024791 created "2023-03-04" @default.
- W4323024791 creator A5024081062 @default.
- W4323024791 creator A5043717512 @default.
- W4323024791 date "2023-01-01" @default.
- W4323024791 modified "2023-09-24" @default.
- W4323024791 title "Public Opinion Assessment Through Grey Relational Analysis Approach" @default.
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- W4323024791 doi "https://doi.org/10.1007/978-981-19-9932-1_5" @default.
- W4323024791 hasPublicationYear "2023" @default.
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