Texas Public Agencies’ Tweets and Public Engagement During the COVID-19 Pandemic: Natural Language Processing Approach

Tang, Lu; Liu, Wenlin; Thomas, Benjamin; Tran, Hong Thoai Nga; Zou, Wenxue; Zhang, Xueying; Zhi, Degui

doi:10.2196/26720

Cited by 28 publications

(34 citation statements)

References 31 publications

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“…The content of the tweets was also significantly associated with public engagement, where tweets related to uncertainty reduction, public reassurance, and warnings received higher levels of engagement. This is consistent with the results of Tang et al [ 54 ], who examined the public health agencies’ tweets in Texas, where tweets that provided information about COVID-19 or described the government’s actions in containing the spread of COVID-19 were found to be more likely to be retweeted. This suggests that as the CERC model indicates, people need this type of information during a public health crisis.…”

Section: Discussionsupporting

confidence: 91%

The Saudi Ministry of Health’s Twitter Communication Strategies and Public Engagement During the COVID-19 Pandemic: Content Analysis Study

Alhassan¹,

AlDossary²

2021

JMIR Public Health Surveill

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Background During a public health crisis such as the current COVID-19 pandemic, governments and health authorities need quick and accurate methods of communicating with the public. While social media can serve as a useful tool for effective communication during disease outbreaks, few studies have elucidated how these platforms are used by the Ministry of Health (MOH) during disease outbreaks in Saudi Arabia. Objective Guided by the Crisis and Emergency Risk Communication model, this study aimed to explore the MOH’s use of Twitter and the public’s engagement during different stages of the COVID-19 pandemic in Saudi Arabia. Methods Tweets and corresponding likes and retweets were extracted from the official Twitter account of the MOH in Saudi Arabia for the period of January 1 through August 31, 2020. Tweets related to COVID-19 were identified; subsequently, content analysis was performed, in which tweets were coded for the following message types: risk messages, warnings, preparations, uncertainty reduction, efficacy, reassurance, and digital health responses. Public engagement was measured by examining the numbers of likes and retweets. The association between outbreak stages and types of messages was assessed, as well as the effect of these messages on public engagement. Results The MOH posted a total of 1393 original tweets during the study period. Of the total tweets, 1293 (92.82%) were related to COVID-19, and 1217 were ultimately included in the analysis. The MOH posted the majority of its tweets (65.89%) during the initial stage of the outbreak. Accordingly, the public showed the highest level of engagement (as indicated by numbers of likes and retweets) during the initial stage. The types of messages sent by the MOH significantly differed across outbreak stages, with messages related to uncertainty reduction, reassurance, and efficacy being prevalent among all stages. Tweet content, media type, and crisis stage influenced the level of public engagement. Engagement was negatively associated with the inclusion of hyperlinks and multimedia files, while higher level of public engagement was associated with the use of hashtags. Tweets related to warnings, uncertainty reduction, and reassurance received high levels of public engagement. Conclusions This study provides insights into the Saudi MOH’s communication strategy during the COVID-19 pandemic. Our results have implications for researchers, governments, health organizations, and practitioners with regard to their communication practices during outbreaks. To increase public engagement, governments and health authorities should consider the public’s need for information. This, in turn, could raise public awareness regarding disease outbreaks.

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Section: Discussionsupporting

confidence: 91%

The Saudi Ministry of Health’s Twitter Communication Strategies and Public Engagement During the COVID-19 Pandemic: Content Analysis Study

Alhassan¹,

AlDossary²

2021

JMIR Public Health Surveill

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“…Moreover, a systematic review also suggests that there is an essential need for an accurate and tested tool for sentiment analysis of tweets using a health care setting [ 30 ]. For example, the natural language processing approach and healthcare-specific corpus of manually annotated tweets were implemented to learn the sentiment from Texas Public Agencies’ tweets and public engagement during the COVID-19 pandemic [ 31 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Emotion diffusion effect: Negative sentiment COVID-19 tweets of public organizations attract more responses from followers

Yang

et al. 2022

PLoS ONE

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Coronavirus disease 2019 (COVID-19) has triggered an enormous number of discussion topics on social media Twitter. It has an impact on the global health system and citizen responses to the pandemic. Multiple responses (replies, favorites, and retweets) reflect the followers’ attitudes and emotions towards these tweets. Twitter data such as these have inspired substantial research interest in sentiment and social trend analyses. To date, studies on Twitter data have focused on the associational relationships between variables in a population. There is a need for further discovery of causality, such as the influence of sentiment polarity of tweet response on further discussion topics. These topics often reflect the human perception of COVID-19. This study addresses this exact topic. It aims to develop a new method to unveil the causal relationships between the sentiment polarity and responses in social media data. We employed sentiment polarity, i.e., positive or negative sentiment, as the treatment variable in this quasi-experimental study. The data is the tweets posted by nine authoritative public organizations in four countries and the World Health Organization from December 1, 2019, to May 10, 2020. Employing the inverse probability weighting model, we identified the treatment effect of sentiment polarity on the multiple responses of tweets. The topics with negative sentiment polarity on COVID-19 attracted significantly more replies (69±49) and favorites (688±677) than the positive tweets. However, no significant difference in the number of retweets was found between the negative and positive tweets. This study contributes a new method for social media analysis. It generates new insight into the influence of sentiment polarity of tweets about COVID-19 on tweet responses.

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“…3) H3: We expect that in counties or parishes with higher socioeconomic conditions, users will be more optimistic about the pandemic. 4) H4: Among the three message functions (action, information, and community) of the government accounts, we expect that action tweets will receive the most engagement as reported in previous studies [7], [8]. Although existing research provides some interesting observations in their analysis of social media data related to COVID-19, there are several limitations based on their data preparation and analysis.…”

Section: Introductionmentioning

confidence: 84%

“…Last but not least, to the best of our knowledge, there is no existing work that analyzes social media posts directly responding to public health messages from government officials. Although some existing works analyze engagement numbers, such as retweet counts, of tweets posted by government officials during the pandemic [7], [8], they do not examine the content of engagement tweets posted by the users such as replies. It is imperative to analyze such targeted social media data to better understand public sentiment related to public health messaging during the pandemic.…”

Section: Introductionmentioning

confidence: 99%

Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. States

et al. 2022

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The abundance of available information on social networks 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 networks, 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.INDEX TERMS COVID-19, geospatial data analysis, natural language processing, public engagement, public health messaging, sentiment analysis, statistical analysis, and Twitter data analytics.

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Texas Public Agencies’ Tweets and Public Engagement During the COVID-19 Pandemic: Natural Language Processing Approach

Cited by 28 publications

References 31 publications

The Saudi Ministry of Health’s Twitter Communication Strategies and Public Engagement During the COVID-19 Pandemic: Content Analysis Study

The Saudi Ministry of Health’s Twitter Communication Strategies and Public Engagement During the COVID-19 Pandemic: Content Analysis Study

Emotion diffusion effect: Negative sentiment COVID-19 tweets of public organizations attract more responses from followers

Analyzing Tweeting Patterns and Public Engagement on Twitter During the Recognition Period of the COVID-19 Pandemic: A Study of Two U.S. States

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