scholarly journals Social Media Images as an Emerging Tool to Monitor Adherence to COVID-19 Public Health Guidelines: A Content Analysis (Preprint)

10.2196/24787 ◽  
2020 ◽  
Author(s):  
Sean Young ◽  
Qingpeng Zheng ◽  
Daniel Dajun Zeng ◽  
Yongcheng Zhan ◽  
William Cumberland
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Media Images

A shift from science to politics : a content analysis of COVID-19 Videos on YouTube (Preprint)

2021 ◽  
Author(s):  
Chyun-Fung Shi ◽  
Matthew C So ◽  
Sophie Stelmach ◽  
Arielle Earn ◽  
David J D Earn ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Large Scale ◽  
Control Measures ◽  
Mitigation Measures ◽  
Health Campaigns ◽  
Public Attention ◽  
Conflicting Information ◽  
Social Media Platforms

BACKGROUND The COVID-19 pandemic is the first pandemic where social media platforms relayed information on a large scale, enabling an “infodemic” of conflicting information which undermined the global response to the pandemic. Understanding how the information circulated and evolved on social media platforms is essential for planning future public health campaigns. OBJECTIVE This study investigated what types of themes about COVID-19 were most viewed on YouTube during the first 8 months of the pandemic, and how COVID-19 themes progressed over this period. METHODS We analyzed top-viewed YouTube COVID-19 related videos in English from from December 1, 2019 to August 16, 2020 with an open inductive content analysis. We coded 536 videos associated with 1.1 billion views across the study period. East Asian countries were the first to report the virus, while most of the top-viewed videos in English were from the US. Videos from straight news outlets dominated the top-viewed videos throughout the outbreak, and public health authorities contributed the fewest. Although straight news was the dominant COVID-19 video source with various types of themes, its viewership per video was similar to that for entertainment news and YouTubers after March. RESULTS We found, first, that collective public attention to the COVID-19 pandemic on YouTube peaked around March 2020, before the outbreak peaked, and flattened afterwards despite a spike in worldwide cases. Second, more videos focused on prevention early on, but videos with political themes increased through time. Third, regarding prevention and control measures, masking received much less attention than lockdown and social distancing in the study period. CONCLUSIONS Our study suggests that a transition of focus from science to politics on social media intensified the COVID-19 infodemic and may have weakened mitigation measures during the first waves of the COVID-19 pandemic. It is recommended that authorities should consider co-operating with reputable social media influencers to promote health campaigns and improve health literacy. In addition, given high levels of globalization of social platforms and polarization of users, tailoring communication towards different digital communities is likely to be essential.

scholarly journals Infodemia and COVID-19: a text mining analysis

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
W De Caro
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Text Mining ◽  
Real Time ◽  
Public Perception ◽  
Health Authorities ◽  
Health Agencies ◽  
Use Of Social Media ◽  
Twitter Activity

Abstract Introduction Covid-19 epidemic lead a huge use of social media to comment and spread information from the widest sources. Infodemia looks at excessive amount of information circulating, which makes it difficult to orientate communities on a given topic due to the difficulty of identifying reliable sources. Using text mining analysis it is possible to identify what drives public conversation and impact of Covid-19. Methods Public perceptions in emergencies is traditionally measured with surveys. However, to have a global sight of the pandemia, Twitter represents a powerful tool which gives real-time monitoring of public perception. The study aimed to: 1) monitor the use of the terms “Covid-19” or “Coronarivus” over time; and 2) to conduct a specific text and sentiment analysis. Results Between January 10 and May 8, 2020, over 600 million tweets were retrieved. Of those 600.000 tweets were randomly selected, coded, and analyzed. About 10% of cases were identified as misinformation. Public figures, experts in public health, and virologists represent the most popular sources in comparison to the official government and health agencies. There is a positive correlation between Twitter activity peaks and COVID-19 infection peaks. Text mining analysis was carried out, as well as a content analysis, also in order to identify changing emotions and sentiments during time. This analysis, particularly during the lockdown, clearly shows that participation on social media can potentially have an effect on building social capital and social support. Conclusions This study confirms that using social media to conduct infodemic studies is an important area of development in public health arena. COVID-19 tweets were primarily used to disseminate information from credible sources, but were also a source of opinions, emotion and experiences. Tweets can be used for real-time content analysis and knowledge translation research, allowing health authorities to respond to public concerns. Key messages Social media is crucial for health information. Infodemia as new way for study health.

scholarly journals Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea

10.2196/18897 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e18897 ◽  
Author(s):  
Han Woo Park ◽  
Sejung Park ◽  
Miyoung Chong
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Network Analysis ◽  
South Korea ◽  
Medical Information ◽  
Systematic Research ◽  
News Frames ◽  
Starting Point ◽  
Significant Difference

Background SARS-CoV-2 (severe acute respiratory coronavirus 2) was spreading rapidly in South Korea at the end of February 2020 following its initial outbreak in China, making Korea the new center of global attention. The role of social media amid the current coronavirus disease (COVID-19) pandemic has often been criticized, but little systematic research has been conducted on this issue. Social media functions as a convenient source of information in pandemic situations. Objective Few infodemiology studies have applied network analysis in conjunction with content analysis. This study investigates information transmission networks and news-sharing behaviors regarding COVID-19 on Twitter in Korea. The real time aggregation of social media data can serve as a starting point for designing strategic messages for health campaigns and establishing an effective communication system during this outbreak. Methods Korean COVID-19-related Twitter data were collected on February 29, 2020. Our final sample comprised of 43,832 users and 78,233 relationships on Twitter. We generated four networks in terms of key issues regarding COVID-19 in Korea. This study comparatively investigates how COVID-19-related issues have circulated on Twitter through network analysis. Next, we classified top news channels shared via tweets. Lastly, we conducted a content analysis of news frames used in the top-shared sources. Results The network analysis suggests that the spread of information was faster in the Coronavirus network than in the other networks (Corona19, Shincheon, and Daegu). People who used the word “Coronavirus” communicated more frequently with each other. The spread of information was faster, and the diameter value was lower than for those who used other terms. Many of the news items highlighted the positive roles being played by individuals and groups, directing readers’ attention to the crisis. Ethical issues such as deviant behavior among the population and an entertainment frame highlighting celebrity donations also emerged often. There was a significant difference in the use of nonportal (n=14) and portal news (n=26) sites between the four network types. The news frames used in the top sources were similar across the networks (P=.89, 95% CI 0.004-0.006). Tweets containing medically framed news articles (mean 7.571, SD 1.988) were found to be more popular than tweets that included news articles adopting nonmedical frames (mean 5.060, SD 2.904; N=40, P=.03, 95% CI 0.169-4.852). Conclusions Most of the popular news on Twitter had nonmedical frames. Nevertheless, the spillover effect of the news articles that delivered medical information about COVID-19 was greater than that of news with nonmedical frames. Social media network analytics cannot replace the work of public health officials; however, monitoring public conversations and media news that propagates rapidly can assist public health professionals in their complex and fast-paced decision-making processes.

scholarly journals Prevalence and Characteristics of Twitter Posts About Court-Ordered, Tobacco-Related Corrective Statements: Descriptive Content Analysis (Preprint)

2018 ◽  
Author(s):  
Dannielle E Kelley ◽  
Meredith Brown ◽  
Alice Murray ◽  
Kelly D Blake
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Health Organizations ◽  
Descriptive Content ◽  
Additional Information ◽  
Philip Morris ◽  
The Social ◽  
Public Health Organizations ◽  
Initial Release

BACKGROUND Three major US tobacco companies were recently ordered to publish corrective statements intended to prevent and restrain further fraud about the health effects of smoking. The court-ordered statements began appearing in newspapers and on television (TV) in late 2017. OBJECTIVE The objective of this study was to examine the social media dissemination of the tobacco corrective statements during the first 6 months of the implementation of the statements. METHODS We conducted a descriptive content analysis of Twitter posts using an iterative search strategy through Crimson Hexagon and randomly selected 19.74% (456/2309) of original posts occurring between November 1, 2017, and March 27, 2018, for coding and analysis. We assessed post volume over time, source or author, valence, linked content, and reference to the industry (eg, big tobacco, tobacco industry, and Philip Morris) and media outlet (TV or newspaper). Retweeted content was coded for source/author and prevalence. RESULTS Most posts were published in November 2017, surrounding the initial release of the corrective statements. Content was generally neutral (58.7%, 268/456) or positive (33.3%, 152/456) in valence, included links to additional information about the statements (94.9%, 433/456), referred to the industry (87.7%, 400/456), and did not mention a specific media channel on which the statements were aired or published (15%). The majority of original posts were created by individual users (55.2%, 252/456), whereas the majority of retweeted posts were posted by public health organizations (51%). Differences by source are reported, for example, organization posts are more likely to include a link to additional information compared with individual users (<italic>P</italic>=.03). CONCLUSIONS Conversations about the court-ordered corrective statements are taking place on Twitter and are generally neutral or positive in nature. Public health organizations may be increasing the prevalence of these conversations through social media engagement.

scholarly journals Health Pandemic and Social Media: A Content Analysis of COVID-Related Posts on a Telegram Channel With More Than One Million Subscribers

2021 ◽  
Author(s):  
Simin Mehdipour ◽  
Nazanin Jannati ◽  
Mozhgan Negarestani ◽  
Saber Amirzadeh ◽  
Sareh Keshvardoost ◽  
...  
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Health Information ◽  
Health Organizations ◽  
Public Health Emergencies

Background: Mobile-based social media play an important role in the dissemination of information during public health emergencies. Objectives: This study aimed to analyze the contents and trends of public messages posted on Telegram during Coronavirus Disease 2019 (COVID-19) pandemic. Methods: A content analysis of the 1781 messages, posted in a public Telegram channel with more than one million subscribers performed over 9-weeks. The messages were categorized into seven categories. Results: In total, 39% (n=703) of all messages were related to COVID-19. With the official confirmation of the case of COVID-19 in Iran, the number of COVID-related massages started to rise. Overall, the most frequent messages were of joke and humor (n=292, 41.5%), followed by educational messages (n=140, 19.9%). Conclusion: Our study showed that the most popular messages during first weeks of COVID pandemic were satirical, indicating that people may not had taken the risks of this pandemic seriously. It is crucial for health organizations to develop strategies for dissemination of reliable health information through social media.

scholarly journals An Instagram-Based Study to Understand Betel Nut Use Culture in Micronesia: Exploratory Content Analysis

10.2196/13954 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e13954
Author(s):  
Wayne Buente ◽  
Francis Dalisay ◽  
Pallav Pokhrel ◽  
Hanae Kurihara Kramer ◽  
Ian Pagano
Keyword(s):  
Public Health ◽  
Social Media ◽  
Substance Use ◽  
Content Analysis ◽  
Social Engagement ◽  
Cultural Context ◽  
World Health ◽  
Betel Nut ◽  
Social Media Platforms ◽  
Health Organization

Background A 2012 World Health Organization report recognizes betel nut use as an urgent public health threat faced by the Western Pacific region. However, compared with other addictive substances, little is known about how betel nuts are depicted on social media platforms. In particular, image-based social media platforms can be powerful tools for health communication. Studying the content of substance use on visual social media may provide valuable insights into public health interventions. Objective This study aimed to explore and document the ways that betel nut is portrayed on the photo-sharing site Instagram. The analysis focuses on the hashtag #pugua, which refers to the local term for betel nut in Guam and other parts of Micronesia. Methods An exploratory content analysis of 242 Instagram posts tagged #pugua was conducted based on previous research on substance use and Instagram and betel nut practices in Micronesia. In addition, the study examined the social engagement of betel nut content on the image-based platform. Results The study findings revealed content themes referencing the betel nut or betel nut tree, betel nut preparation practices, and the unique social and cultural context surrounding betel nut activity in Guam and Micronesia. In addition, certain practices and cultural themes encouraged social engagement on Instagram. Conclusions The findings from this study emphasize the cultural relevance of betel nut use in Micronesia. These findings provide a basis for empirically testing hypotheses related to the etiological roles of cultural identity and pride in shaping betel nut use behavior among Micronesians, particularly youths and young adults. Such research is likely to inform the development of culturally relevant betel nut prevention and cessation programs.

scholarly journals A Psycholinguistic Analysis of Responses to Live-Stream Suicides on Social Media

2019 ◽  
Vol 16 (16) ◽  
pp. 2848
Author(s):  
Ang Li ◽  
Dongdong Jiao ◽  
Xingyun Liu ◽  
Jiumo Sun ◽  
Tingshao Zhu
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Suicide Prevention ◽  
Crisis Intervention ◽  
Public Health Problem ◽  
Classification Models ◽  
Analysis Methods ◽  
Key Features ◽  
F Measure

Live-stream suicide has become an emerging public health problem in many countries. Regular users are often the first to witness and respond to such suicides, emphasizing their impact on the success of crisis intervention. In order to reduce the likelihood of suicide deaths, this paper aims to use psycholinguistic analysis methods to facilitate automatic detection of negative expressions in responses to live-stream suicides on social media. In this paper, a total of 7212 comments posted on suicide-related messages were collected and analyzed. First, a content analysis was performed to investigate the nature of each comment (negative or not). Second, the simplified Chinese version of the LIWC software was used to extract 75 psycholinguistic features from each comment. Third, based on 19 selected key features, four classification models were established to differentiate between comments with and without negative expressions. Results showed that 19.55% of 7212 comments were recognized as “making negative responses”. Among the four classification models, the highest values of Precision, Recall, F-Measure, and Screening Efficacy reached 69.8%, 85.9%, 72.9%, and 47.1%, respectively. This paper confirms the need for campaigns to reduce negative responses to live-stream suicides and support the use of psycholinguistic analysis methods to improve suicide prevention efforts.

scholarly journals Conversations and Medical News Frames on Twitter: Infodemiological Study on COVID-19 in South Korea (Preprint)

2020 ◽  
Author(s):  
Han Woo Park ◽  
Sejung Park ◽  
Miyoung Chong
Keyword(s):  
Public Health ◽  
Social Media ◽  
Content Analysis ◽  
Network Analysis ◽  
South Korea ◽  
Medical Information ◽  
Systematic Research ◽  
News Frames ◽  
Starting Point ◽  
Significant Difference

BACKGROUND SARS-CoV-2 (severe acute respiratory coronavirus 2) was spreading rapidly in South Korea at the end of February 2020 following its initial outbreak in China, making Korea the new center of global attention. The role of social media amid the current coronavirus disease (COVID-19) pandemic has often been criticized, but little systematic research has been conducted on this issue. Social media functions as a convenient source of information in pandemic situations. OBJECTIVE Few infodemiology studies have applied network analysis in conjunction with content analysis. This study investigates information transmission networks and news-sharing behaviors regarding COVID-19 on Twitter in Korea. The real time aggregation of social media data can serve as a starting point for designing strategic messages for health campaigns and establishing an effective communication system during this outbreak. METHODS Korean COVID-19-related Twitter data were collected on February 29, 2020. Our final sample comprised of 43,832 users and 78,233 relationships on Twitter. We generated four networks in terms of key issues regarding COVID-19 in Korea. This study comparatively investigates how COVID-19-related issues have circulated on Twitter through network analysis. Next, we classified top news channels shared via tweets. Lastly, we conducted a content analysis of news frames used in the top-shared sources. RESULTS The network analysis suggests that the spread of information was faster in the Coronavirus network than in the other networks (Corona19, Shincheon, and Daegu). People who used the word “Coronavirus” communicated more frequently with each other. The spread of information was faster, and the diameter value was lower than for those who used other terms. Many of the news items highlighted the positive roles being played by individuals and groups, directing readers’ attention to the crisis. Ethical issues such as deviant behavior among the population and an entertainment frame highlighting celebrity donations also emerged often. There was a significant difference in the use of nonportal (n=14) and portal news (n=26) sites between the four network types. The news frames used in the top sources were similar across the networks (<i>P</i>=.89, 95% CI 0.004-0.006). Tweets containing medically framed news articles (mean 7.571, SD 1.988) were found to be more popular than tweets that included news articles adopting nonmedical frames (mean 5.060, SD 2.904; N=40, <i>P</i>=.03, 95% CI 0.169-4.852). CONCLUSIONS Most of the popular news on Twitter had nonmedical frames. Nevertheless, the spillover effect of the news articles that delivered medical information about COVID-19 was greater than that of news with nonmedical frames. Social media network analytics cannot replace the work of public health officials; however, monitoring public conversations and media news that propagates rapidly can assist public health professionals in their complex and fast-paced decision-making processes.

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