Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. States
The abundance of available information on social media can provide invaluable insights into people’s responses to health information and public health guidance concerning COVID-19. This study examines tweeting patterns and public engagement on Twitter, as forms of social media, related to...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9825632/ |
| _version_ | 1811293307861467136 |
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| author | Misbah Ul Hoque Kisung Lee Jessica L. Beyer Sara R. Curran Katie S. Gonser Nina S. N. Lam Volodymyr V. Mihunov Kejin Wang |
| author_facet | Misbah Ul Hoque Kisung Lee Jessica L. Beyer Sara R. Curran Katie S. Gonser Nina S. N. Lam Volodymyr V. Mihunov Kejin Wang |
| author_sort | Misbah Ul Hoque |
| collection | DOAJ |
| description | The abundance of available information on social media can provide invaluable insights into people’s responses to health information and public health guidance concerning COVID-19. This study examines tweeting patterns and public engagement on Twitter, as forms of social media, related to public health messaging in two U.S. states (Washington and Louisiana) during the early stage of the pandemic. We analyze more than 7M tweets and 571K COVID-19-related tweets posted by users in the two states over the first 25 days of the pandemic in the U.S. (Feb. 23, 2020, to Mar. 18, 2020). We also qualitatively code and examine 460 tweets posted by selected governmental official accounts during the same period for public engagement analysis. We use various methods for analyzing the data, including statistical analysis, sentiment analysis, and word usage metrics, to find inter- and intra-state disparities of tweeting patterns and public engagement with health messaging. Our findings reveal that users in Washington were more active on Twitter than users in Louisiana in terms of the total number and density of COVID-19-related tweets during the early stage of the pandemic. Our correlation analysis results for counties or parishes show that the Twitter activities (tweet density, COVID-19 tweet density, and user density) were positively correlated with population density in both states at the 0.01 level of significance. Our sentiment analysis results demonstrate that the average daily sentiment scores of all and COVID-19-related tweets in Washington were consistently higher than those in Louisiana during this period. While the daily average sentiment scores of COVID-19-related tweets were in the negative range, the scores of all tweets were in the positive range in both states. Lastly, our analysis of governmental Twitter accounts found that these accounts’ messages were most commonly meant to spread information about the pandemic, but that users were most likely to engage with tweets that requested readers take action, such as hand washing. |
| first_indexed | 2024-04-13T04:59:26Z |
| format | Article |
| id | doaj.art-fbc79e75829549d0a387ef1fe3c9585f |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T04:59:26Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-fbc79e75829549d0a387ef1fe3c9585f2022-12-22T03:01:24ZengIEEEIEEE Access2169-35362022-01-0110728797289410.1109/ACCESS.2022.31896709825632Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. StatesMisbah Ul Hoque0https://orcid.org/0000-0001-9354-7838Kisung Lee1https://orcid.org/0000-0003-4367-4374Jessica L. Beyer2Sara R. Curran3https://orcid.org/0000-0001-9353-4287Katie S. Gonser4Nina S. N. Lam5https://orcid.org/0000-0002-5344-9368Volodymyr V. Mihunov6Kejin Wang7https://orcid.org/0000-0001-8736-4955Division of Computer Science and Engineering, Louisiana State University, Baton Rouge, LA, USADivision of Computer Science and Engineering, Louisiana State University, Baton Rouge, LA, USAThe Henry M. Jackson School of International Studies, University of Washington, Seattle, WA, USAThe Henry M. Jackson School of International Studies, University of Washington, Seattle, WA, USAThe Henry M. Jackson School of International Studies, University of Washington, Seattle, WA, USADepartment of Environmental Sciences, Louisiana State University, Baton Rouge, LA, USADepartment of Environmental Sciences, Louisiana State University, Baton Rouge, LA, USADepartment of Environmental Sciences, Louisiana State University, Baton Rouge, LA, USAThe abundance of available information on social media can provide invaluable insights into people’s responses to health information and public health guidance concerning COVID-19. This study examines tweeting patterns and public engagement on Twitter, as forms of social media, related to public health messaging in two U.S. states (Washington and Louisiana) during the early stage of the pandemic. We analyze more than 7M tweets and 571K COVID-19-related tweets posted by users in the two states over the first 25 days of the pandemic in the U.S. (Feb. 23, 2020, to Mar. 18, 2020). We also qualitatively code and examine 460 tweets posted by selected governmental official accounts during the same period for public engagement analysis. We use various methods for analyzing the data, including statistical analysis, sentiment analysis, and word usage metrics, to find inter- and intra-state disparities of tweeting patterns and public engagement with health messaging. Our findings reveal that users in Washington were more active on Twitter than users in Louisiana in terms of the total number and density of COVID-19-related tweets during the early stage of the pandemic. Our correlation analysis results for counties or parishes show that the Twitter activities (tweet density, COVID-19 tweet density, and user density) were positively correlated with population density in both states at the 0.01 level of significance. Our sentiment analysis results demonstrate that the average daily sentiment scores of all and COVID-19-related tweets in Washington were consistently higher than those in Louisiana during this period. While the daily average sentiment scores of COVID-19-related tweets were in the negative range, the scores of all tweets were in the positive range in both states. Lastly, our analysis of governmental Twitter accounts found that these accounts’ messages were most commonly meant to spread information about the pandemic, but that users were most likely to engage with tweets that requested readers take action, such as hand washing.https://ieeexplore.ieee.org/document/9825632/COVID-19geospatial data analysisnatural language processingpublic engagementpublic health messagingsentiment analysis |
| spellingShingle | Misbah Ul Hoque Kisung Lee Jessica L. Beyer Sara R. Curran Katie S. Gonser Nina S. N. Lam Volodymyr V. Mihunov Kejin Wang Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. States IEEE Access COVID-19 geospatial data analysis natural language processing public engagement public health messaging sentiment analysis |
| title | Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. States |
| title_full | Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. States |
| title_fullStr | Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. States |
| title_full_unstemmed | Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. States |
| title_short | Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. States |
| title_sort | analyzing tweeting patterns and public engagement on twitter during the recognition period of the covid 19 pandemic a study of two u s states |
| topic | COVID-19 geospatial data analysis natural language processing public engagement public health messaging sentiment analysis |
| url | https://ieeexplore.ieee.org/document/9825632/ |
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