Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis
BackgroundThe development and approval of COVID-19 vaccines have generated optimism for the end of the COVID-19 pandemic and a return to normalcy. However, vaccine hesitancy, often fueled by misinformation, poses a major barrier to achieving herd immunity. Objecti...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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JMIR Publications
2022-03-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2022/3/e35016 |
| _version_ | 1797735234412740608 |
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| author | Hyeju Jang Emily Rempel Ian Roe Prince Adu Giuseppe Carenini Naveed Zafar Janjua |
| author_facet | Hyeju Jang Emily Rempel Ian Roe Prince Adu Giuseppe Carenini Naveed Zafar Janjua |
| author_sort | Hyeju Jang |
| collection | DOAJ |
| description |
BackgroundThe development and approval of COVID-19 vaccines have generated optimism for the end of the COVID-19 pandemic and a return to normalcy. However, vaccine hesitancy, often fueled by misinformation, poses a major barrier to achieving herd immunity.
ObjectiveWe aim to investigate Twitter users’ attitudes toward COVID-19 vaccination in Canada after vaccine rollout.
MethodsWe applied a weakly supervised aspect-based sentiment analysis (ABSA) technique, which involves the human-in-the-loop system, on COVID-19 vaccination–related tweets in Canada. Automatically generated aspect and opinion terms were manually corrected by public health experts to ensure the accuracy of the terms and make them more domain-specific. Then, based on these manually corrected terms, the system inferred sentiments toward the aspects. We observed sentiments toward key aspects related to COVID-19 vaccination, and investigated how sentiments toward “vaccination” changed over time. In addition, we analyzed the most retweeted or liked tweets by observing most frequent nouns and sentiments toward key aspects.
ResultsAfter applying the ABSA system, we obtained 170 aspect terms (eg, “immunity” and “pfizer”) and 6775 opinion terms (eg, “trustworthy” for the positive sentiment and “jeopardize” for the negative sentiment). While manually verifying or editing these terms, our public health experts selected 20 key aspects related to COVID-19 vaccination for analysis. The sentiment analysis results for the 20 key aspects revealed negative sentiments related to “vaccine distribution,” “side effects,” “allergy,” “reactions,” and “anti-vaxxer,” and positive sentiments related to “vaccine campaign,” “vaccine candidates,” and “immune response.” These results indicate that the Twitter users express concerns about the safety of vaccines but still consider vaccines as the option to end the pandemic. In addition, compared to the sentiment of the remaining tweets, the most retweeted or liked tweets showed more positive sentiment overall toward key aspects (P<.001), especially vaccines (P<.001) and vaccination (P=.009). Further investigation of the most retweeted or liked tweets revealed two opposing trends in Twitter users who showed negative sentiments toward vaccines: the “anti-vaxxer” population that used negative sentiments as a means to discourage vaccination and the “Covid Zero” population that used negative sentiments to encourage vaccinations while critiquing the public health response.
ConclusionsOur study examined public sentiments toward COVID-19 vaccination on tweets over an extended period in Canada. Our findings could inform public health agencies to design and implement interventions to promote vaccination. |
| first_indexed | 2024-03-12T12:56:04Z |
| format | Article |
| id | doaj.art-f1d81294926c46c8bae4c8d2d3da7476 |
| institution | Directory Open Access Journal |
| issn | 1438-8871 |
| language | English |
| last_indexed | 2024-03-12T12:56:04Z |
| publishDate | 2022-03-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj.art-f1d81294926c46c8bae4c8d2d3da74762023-08-28T21:10:45ZengJMIR PublicationsJournal of Medical Internet Research1438-88712022-03-01243e3501610.2196/35016Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment AnalysisHyeju Janghttps://orcid.org/0000-0002-7652-1158Emily Rempelhttps://orcid.org/0000-0002-9473-3533Ian Roehttps://orcid.org/0000-0002-9278-4951Prince Aduhttps://orcid.org/0000-0002-3983-0875Giuseppe Careninihttps://orcid.org/0000-0003-4310-0119Naveed Zafar Janjuahttps://orcid.org/0000-0001-5681-719X BackgroundThe development and approval of COVID-19 vaccines have generated optimism for the end of the COVID-19 pandemic and a return to normalcy. However, vaccine hesitancy, often fueled by misinformation, poses a major barrier to achieving herd immunity. ObjectiveWe aim to investigate Twitter users’ attitudes toward COVID-19 vaccination in Canada after vaccine rollout. MethodsWe applied a weakly supervised aspect-based sentiment analysis (ABSA) technique, which involves the human-in-the-loop system, on COVID-19 vaccination–related tweets in Canada. Automatically generated aspect and opinion terms were manually corrected by public health experts to ensure the accuracy of the terms and make them more domain-specific. Then, based on these manually corrected terms, the system inferred sentiments toward the aspects. We observed sentiments toward key aspects related to COVID-19 vaccination, and investigated how sentiments toward “vaccination” changed over time. In addition, we analyzed the most retweeted or liked tweets by observing most frequent nouns and sentiments toward key aspects. ResultsAfter applying the ABSA system, we obtained 170 aspect terms (eg, “immunity” and “pfizer”) and 6775 opinion terms (eg, “trustworthy” for the positive sentiment and “jeopardize” for the negative sentiment). While manually verifying or editing these terms, our public health experts selected 20 key aspects related to COVID-19 vaccination for analysis. The sentiment analysis results for the 20 key aspects revealed negative sentiments related to “vaccine distribution,” “side effects,” “allergy,” “reactions,” and “anti-vaxxer,” and positive sentiments related to “vaccine campaign,” “vaccine candidates,” and “immune response.” These results indicate that the Twitter users express concerns about the safety of vaccines but still consider vaccines as the option to end the pandemic. In addition, compared to the sentiment of the remaining tweets, the most retweeted or liked tweets showed more positive sentiment overall toward key aspects (P<.001), especially vaccines (P<.001) and vaccination (P=.009). Further investigation of the most retweeted or liked tweets revealed two opposing trends in Twitter users who showed negative sentiments toward vaccines: the “anti-vaxxer” population that used negative sentiments as a means to discourage vaccination and the “Covid Zero” population that used negative sentiments to encourage vaccinations while critiquing the public health response. ConclusionsOur study examined public sentiments toward COVID-19 vaccination on tweets over an extended period in Canada. Our findings could inform public health agencies to design and implement interventions to promote vaccination.https://www.jmir.org/2022/3/e35016 |
| spellingShingle | Hyeju Jang Emily Rempel Ian Roe Prince Adu Giuseppe Carenini Naveed Zafar Janjua Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis Journal of Medical Internet Research |
| title | Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis |
| title_full | Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis |
| title_fullStr | Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis |
| title_full_unstemmed | Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis |
| title_short | Tracking Public Attitudes Toward COVID-19 Vaccination on Tweets in Canada: Using Aspect-Based Sentiment Analysis |
| title_sort | tracking public attitudes toward covid 19 vaccination on tweets in canada using aspect based sentiment analysis |
| url | https://www.jmir.org/2022/3/e35016 |
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