Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets
BackgroundIn the current phase of the COVID-19 pandemic, we are witnessing the most massive vaccine rollout in human history. Like any other drug, vaccines may cause unexpected side effects, which need to be investigated in a timely manner to minimize harm in the population....
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2022-05-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2022/5/e35115 |
| _version_ | 1797735052063277056 |
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| author | Beatrice Portelli Simone Scaboro Roberto Tonino Emmanuele Chersoni Enrico Santus Giuseppe Serra |
| author_facet | Beatrice Portelli Simone Scaboro Roberto Tonino Emmanuele Chersoni Enrico Santus Giuseppe Serra |
| author_sort | Beatrice Portelli |
| collection | DOAJ |
| description |
BackgroundIn the current phase of the COVID-19 pandemic, we are witnessing the most massive vaccine rollout in human history. Like any other drug, vaccines may cause unexpected side effects, which need to be investigated in a timely manner to minimize harm in the population. If not properly dealt with, side effects may also impact public trust in the vaccination campaigns carried out by national governments.
ObjectiveMonitoring social media for the early identification of side effects, and understanding the public opinion on the vaccines are of paramount importance to ensure a successful and harmless rollout. The objective of this study was to create a web portal to monitor the opinion of social media users on COVID-19 vaccines, which can offer a tool for journalists, scientists, and users alike to visualize how the general public is reacting to the vaccination campaign.
MethodsWe developed a tool to analyze the public opinion on COVID-19 vaccines from Twitter, exploiting, among other techniques, a state-of-the-art system for the identification of adverse drug events on social media; natural language processing models for sentiment analysis; statistical tools; and open-source databases to visualize the trending hashtags, news articles, and their factuality. All modules of the system are displayed through an open web portal.
ResultsA set of 650,000 tweets was collected and analyzed in an ongoing process that was initiated in December 2020. The results of the analysis are made public on a web portal (updated daily), together with the processing tools and data. The data provide insights on public opinion about the vaccines and its change over time. For example, users show a high tendency to only share news from reliable sources when discussing COVID-19 vaccines (98% of the shared URLs). The general sentiment of Twitter users toward the vaccines is negative/neutral; however, the system is able to record fluctuations in the attitude toward specific vaccines in correspondence with specific events (eg, news about new outbreaks). The data also show how news coverage had a high impact on the set of discussed topics. To further investigate this point, we performed a more in-depth analysis of the data regarding the AstraZeneca vaccine. We observed how media coverage of blood clot–related side effects suddenly shifted the topic of public discussions regarding both the AstraZeneca and other vaccines. This became particularly evident when visualizing the most frequently discussed symptoms for the vaccines and comparing them month by month.
ConclusionsWe present a tool connected with a web portal to monitor and display some key aspects of the public’s reaction to COVID-19 vaccines. The system also provides an overview of the opinions of the Twittersphere through graphic representations, offering a tool for the extraction of suspected adverse events from tweets with a deep learning model. |
| first_indexed | 2024-03-12T12:53:26Z |
| format | Article |
| id | doaj.art-5203723ec5b84560b284828722728b24 |
| institution | Directory Open Access Journal |
| issn | 1438-8871 |
| language | English |
| last_indexed | 2024-03-12T12:53:26Z |
| publishDate | 2022-05-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj.art-5203723ec5b84560b284828722728b242023-08-28T21:46:41ZengJMIR PublicationsJournal of Medical Internet Research1438-88712022-05-01245e3511510.2196/35115Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of TweetsBeatrice Portellihttps://orcid.org/0000-0001-8887-616XSimone Scaborohttps://orcid.org/0000-0003-2533-1298Roberto Toninohttps://orcid.org/0000-0001-7630-7330Emmanuele Chersonihttps://orcid.org/0000-0001-8742-0451Enrico Santushttps://orcid.org/0000-0002-7327-2731Giuseppe Serrahttps://orcid.org/0000-0002-4269-4501 BackgroundIn the current phase of the COVID-19 pandemic, we are witnessing the most massive vaccine rollout in human history. Like any other drug, vaccines may cause unexpected side effects, which need to be investigated in a timely manner to minimize harm in the population. If not properly dealt with, side effects may also impact public trust in the vaccination campaigns carried out by national governments. ObjectiveMonitoring social media for the early identification of side effects, and understanding the public opinion on the vaccines are of paramount importance to ensure a successful and harmless rollout. The objective of this study was to create a web portal to monitor the opinion of social media users on COVID-19 vaccines, which can offer a tool for journalists, scientists, and users alike to visualize how the general public is reacting to the vaccination campaign. MethodsWe developed a tool to analyze the public opinion on COVID-19 vaccines from Twitter, exploiting, among other techniques, a state-of-the-art system for the identification of adverse drug events on social media; natural language processing models for sentiment analysis; statistical tools; and open-source databases to visualize the trending hashtags, news articles, and their factuality. All modules of the system are displayed through an open web portal. ResultsA set of 650,000 tweets was collected and analyzed in an ongoing process that was initiated in December 2020. The results of the analysis are made public on a web portal (updated daily), together with the processing tools and data. The data provide insights on public opinion about the vaccines and its change over time. For example, users show a high tendency to only share news from reliable sources when discussing COVID-19 vaccines (98% of the shared URLs). The general sentiment of Twitter users toward the vaccines is negative/neutral; however, the system is able to record fluctuations in the attitude toward specific vaccines in correspondence with specific events (eg, news about new outbreaks). The data also show how news coverage had a high impact on the set of discussed topics. To further investigate this point, we performed a more in-depth analysis of the data regarding the AstraZeneca vaccine. We observed how media coverage of blood clot–related side effects suddenly shifted the topic of public discussions regarding both the AstraZeneca and other vaccines. This became particularly evident when visualizing the most frequently discussed symptoms for the vaccines and comparing them month by month. ConclusionsWe present a tool connected with a web portal to monitor and display some key aspects of the public’s reaction to COVID-19 vaccines. The system also provides an overview of the opinions of the Twittersphere through graphic representations, offering a tool for the extraction of suspected adverse events from tweets with a deep learning model.https://www.jmir.org/2022/5/e35115 |
| spellingShingle | Beatrice Portelli Simone Scaboro Roberto Tonino Emmanuele Chersoni Enrico Santus Giuseppe Serra Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets Journal of Medical Internet Research |
| title | Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets |
| title_full | Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets |
| title_fullStr | Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets |
| title_full_unstemmed | Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets |
| title_short | Monitoring User Opinions and Side Effects on COVID-19 Vaccines in the Twittersphere: Infodemiology Study of Tweets |
| title_sort | monitoring user opinions and side effects on covid 19 vaccines in the twittersphere infodemiology study of tweets |
| url | https://www.jmir.org/2022/5/e35115 |
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