During the COVID-19 pandemic, social networks were flooded with overwhelming information. This study focused on the interaction between science and society as this took place via Twitter. State of the art algorithmic sentiment analysis was employed to examine the communication between pharmaceutical companies and the public, to analyze the profile of the posts originating from the pharmaceutical companies and to highlight the users’ response to the conveyed messages. Findings indicate the promotion of a positive agenda by the pharmaceutical companies which spawned variable reactions from the users. The predominant part of the public’s response consisted of retweets that endorsed the positive attitude of the companies while the users that responded with actions of higher level of determination such as quotes or replies, enhanced mostly the circulation of messages representing emotions of surprise and fear. The results of our analysis are in accordance with recent general studies of sentiment analysis during the pandemic.
Interaction Between Pharmaceutical Companies and the Public During the COVID-19 Pandemic—A Twitter Analysis
Pecchia L.;
2024-01-01
Abstract
During the COVID-19 pandemic, social networks were flooded with overwhelming information. This study focused on the interaction between science and society as this took place via Twitter. State of the art algorithmic sentiment analysis was employed to examine the communication between pharmaceutical companies and the public, to analyze the profile of the posts originating from the pharmaceutical companies and to highlight the users’ response to the conveyed messages. Findings indicate the promotion of a positive agenda by the pharmaceutical companies which spawned variable reactions from the users. The predominant part of the public’s response consisted of retweets that endorsed the positive attitude of the companies while the users that responded with actions of higher level of determination such as quotes or replies, enhanced mostly the circulation of messages representing emotions of surprise and fear. The results of our analysis are in accordance with recent general studies of sentiment analysis during the pandemic.File | Dimensione | Formato | |
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