scholarly journals What Arguments against COVID-19 Vaccines Run on Facebook in Poland: Content Analysis of Comments

Vaccines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 481
Author(s):  
Dominik Wawrzuta ◽  
Mariusz Jaworski ◽  
Joanna Gotlib ◽  
Mariusz Panczyk
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Real Time ◽  
Vaccine Hesitancy ◽  
European Medicines Agency ◽  
Real Time Monitoring ◽  
Over Time

Social media allow anti-vaxxers to quickly spread misinformation and false statements. This situation may lead to an increase in vaccine hesitancy. We wanted to characterize what arguments against COVID-19 vaccines run on Facebook in Poland. We analyzed Facebook comments related to the five events of the introduction of COVID-19 vaccines—announcements of the efficacy of the Pfizer-BioNTech (09.11.2020), Moderna (16.11.2020), and AstraZeneca (23.11.2020) vaccines, registration of the Pfizer-BioNTech vaccine by the European Medicines Agency (21.12.2020), and the first vaccination in Poland (27.12.2020). We collected the comments from fanpages of the biggest Polish media and then established their main anti-vaccine themes. We found that the negative arguments about COVID-19 vaccines can be divided into 12 categories. Seven of them are universal and also apply to other vaccines but five are new and COVID-19’ specific. The frequency of arguments from a given category varied over time. We also noticed that, while the comments were mostly negative, the reactions were positive. Created codebook of anti-vaccine COVID-19 arguments can be used to monitor the attitude of society towards COVID-19 vaccines. Real-time monitoring of social media is important because the popularity of certain arguments on Facebook changes rapidly over time.

When news media and social media meet: How Facebook users reacted to news stories about a supermarket plastic bag ban

2020 ◽  
pp. 146144482095668
Author(s):  
Kim Borg ◽  
Jo Lindsay ◽  
Jim Curtis
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Environmental Policy ◽  
Social Norms ◽  
Real Time ◽  
News Media ◽  
Plastic Pollution ◽  
News Stories ◽  
Plastic Bag ◽  
Contemporary Media

Plastic reduction policies are important for addressing plastic pollution however, the success of such policies relies on establishing new social norms. This study advances knowledge on public expressions of social norms by exploring the interplay between news media and social media in response to a new environmental policy. It is the first study to explore this phenomenon with the explicit aim of identifying and comparing information related to social norms. A content analysis was conducted in relation to the 2018 Australian supermarket plastic bag ban. Results demonstrate how social norms related to a new policy are created, reinforced and expressed in the contemporary media landscape. The interaction between news media and social media offers a window into public expressions of social norms, where social media provides a platform for civic participation in a public and real-time environment in which users can challenge the dominant narrative presented by the news media.

scholarly journals Digital health for real-time monitoring of a national immunisation campaign in Indonesia: a large-scale effectiveness evaluation

BMJ Open ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. e038282
Author(s):  
Hafizah Jusril ◽  
Iwan Ariawan ◽  
Rita Damayanti ◽  
Lutfan Lazuardi ◽  
Miriam Musa ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Health Workers ◽  
Digital Health ◽  
Ease Of Use ◽  
Qualitative Assessment ◽  
Vaccine Hesitancy ◽  
Real Time Monitoring ◽  
Risk Profiles ◽  
National Immunisation

ObjectiveTo assess the contribution of a digital health real-time monitoring platform towards the achievement of coverage targets during a national immunisation campaign in Indonesia.InterventionsA digital health platform was introduced to facilitate real-time reporting and data visualisation. Health workers submitted reports of children immunised each day by geolocation using mobile phones. Automated reports were generated for programme managers at all levels to enable early responses to coverage gaps.MethodsRisk profiles were generated for each district to assess precampaign immunisation programme performance. Digital health platform use and progress towards targets were monitored continuously throughout the campaign. Study outcomes were total coverage and time to achieve full (100%) coverage. Kaplan-Meier, Cox and linear regression analyses were used to estimate the associations and outcomes after adjusting for district risk profiles. A complementary qualitative assessment explored user experiences and acceptance through interviews with vaccinators and programme managers in provinces and districts selected through multistage random sampling.ResultsBetween August and December 2018, 6462 health facilities registered to use the digital health platform across 28 provinces and 395 districts. After adjusting for precampaign district risk profile and intracampaign delays due to vaccine hesitancy, districts with greater platform utilisation demonstrated higher coverage overall (R2=0.28, p<0.0001) and a shorter interval to achieving full coverage (>75% reporting compliance; Risk Ratio 15.4, 95% CI 5.8 to 40.6). Stronger effects were observed among districts experiencing implementation delays due to vaccine hesitancy. Results from 106 key informant interviews conducted in 6 provinces and 18 districts suggest high degrees of acceptability, ease of use and satisfaction.ConclusionA digital health platform introduced for real-time monitoring of a national immunisation campaign in Indonesia was feasible, well liked and associated with improved problem solving and programme performance, particularly among districts affected by vaccine hesitancy.Trial registration numberISRCTN10850448.

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 Negative e-WOM Resulting from Political Posts on Social Media: A Case Study of a Small Retailer’s Struggle over Time

2021 ◽  
Vol 10 (9) ◽  
pp. 318
Author(s):  
Jennifer Johnson Jorgensen ◽  
Katelyn Sorensen
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Single Case ◽  
Retail Store ◽  
The Political ◽  
Customer Reviews ◽  
Political Opinion ◽  
Political Opinions ◽  
Over Time

Consumers have been advocating for a variety of causes, and in turn, retailers are expressing their political opinions through social-media posts in hopes of aligning with their customers’ views. This study looks at a single case in which customers reacted to a retailer’s political opinion posted on a social media account. Data was collected at the time of the retailer’s political post and up to three years afterward. Content analysis was employed to identify themes from the customer reviews posted, and four themes were identified. Of significance, this study found that customers of a retail store typically merge feelings on the retailer’s product and political post or the retailer’s service and the political post within their social media responses. Thus, a majority of customers in this case were not exclusively focused on battling the political post on social media. Also, a shift in customers’ opinions of the retailer shifted positively over time.

scholarly journals Vaccine hesitancy and anti-vaccination attitudes during the start of COVID-19 vaccination program: a content analysis on Twitter data

2021 ◽  
Author(s):  
Hüseyin Küçükali ◽  
Ömer Ataç ◽  
Ayşe Zülal Tokaç ◽  
Ayşe Seval Palteki ◽  
Osman Erol Hayran
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
World Health ◽  
Vaccine Hesitancy ◽  
Analysis Method ◽  
Conspiracy Theories ◽  
Health Authorities ◽  
Content Analysis Method ◽  
Health Organization

Background: Vaccine hesitation, which is defined as one of the most important global health threats by World Health Organization, maintains its universal importance during the COVID-19 period. Due to the increasing appearance of anti-vaccine arguments on social media, Twitter is a useful resource in detecting these contents. In this study, we aimed to identify the prominent themes about vaccine hesitancy and refusal on social media during the COVID-19 pandemic. Methods: In this qualitative study we collected Twitter contents which contain a vaccine-related keywords and published publicly between 9/12/2020 and 8/1/2021 (n=551,245). A stratified random sample (n=1041) is selected and analyzed by four researchers with content analysis method. Results: All tweets included in the study were shared from 1,000 unique accounts of which 2.7% were verified and 11.3% organizational users. 90.5% of the tweets were about vaccines, 22.6% (n=213) of the tweets mentioned at least one COVID-19 vaccine name and the most frequently mentioned COVID-19 vaccine was CorronaVac (51.2%). Yet, it was mostly as "Chinese vaccine" (42.3%). 22.0% (n=207) of the tweets included at least one anti-vaccination theme. Among tweets that included an anti-vaccination theme; poor scientific processes (21.7%), conspiracy theories (16.4%), and suspicions towards manufacturers (15.5%) were the most frequently mentioned themes. The most co-occurred themes were "Poor scientific process" theme come along with "suspicion towards manufacturers" (n=9) and "suspicion towards health authorities" (n=5). Conclusions: This study may be helpful for health managers to identify the major concerns of the population and organize the preventive measures, through the significant role of social media on early information about vaccine hesitancy and anti-vaccination attitudes.

scholarly journals Analyzing Social Media to Explore the Attitudes and Behaviors Following the Announcement of Successful COVID-19 Vaccine Trials: Infodemiology Study

10.2196/28800 ◽  
2021 ◽  
Vol 1 (1) ◽  
pp. e28800
Author(s):  
Jean-Christophe Boucher ◽  
Kirsten Cornelson ◽  
Jamie L Benham ◽  
Madison M Fullerton ◽  
Theresa Tang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Content Analysis ◽  
Social Network ◽  
Multinational Corporations ◽  
Vaccine Hesitancy ◽  
Media Content ◽  
Media Content Analysis ◽  
Vaccine Trials ◽  
The Government

Background The rollout of COVID-19 vaccines has brought vaccine hesitancy to the forefront in managing this pandemic. COVID-19 vaccine hesitancy is fundamentally different from that of other vaccines due to the new technologies being used, rapid development, and widespread global distribution. Attitudes on vaccines are largely driven by online information, particularly information on social media. The first step toward influencing attitudes about immunization is understanding the current patterns of communication that characterize the immunization debate on social media platforms. Objective We aimed to evaluate societal attitudes, communication trends, and barriers to COVID-19 vaccine uptake through social media content analysis to inform communication strategies promoting vaccine acceptance. Methods Social network analysis (SNA) and unsupervised machine learning were used to characterize COVID-19 vaccine content on Twitter globally. Tweets published in English and French were collected through the Twitter application programming interface between November 19 and 26, 2020, just following the announcement of initial COVID-19 vaccine trials. SNA was used to identify social media clusters expressing mistrustful opinions on COVID-19 vaccination. Based on the SNA results, an unsupervised machine learning approach to natural language processing using a sentence-level algorithm transfer function to detect semantic textual similarity was performed in order to identify the main themes of vaccine hesitancy. Results The tweets (n=636,516) identified that the main themes driving the vaccine hesitancy conversation were concerns of safety, efficacy, and freedom, and mistrust in institutions (either the government or multinational corporations). A main theme was the safety and efficacy of mRNA technology and side effects. The conversation around efficacy was that vaccines were unlikely to completely rid the population of COVID-19, polymerase chain reaction testing is flawed, and there is no indication of long-term T-cell immunity for COVID-19. Nearly one-third (45,628/146,191, 31.2%) of the conversations on COVID-19 vaccine hesitancy clusters expressed concerns for freedom or mistrust of institutions (either the government or multinational corporations) and nearly a quarter (34,756/146,191, 23.8%) expressed criticism toward the government’s handling of the pandemic. Conclusions Social media content analysis combined with social network analysis provides insights into the themes of the vaccination conversation on Twitter. The themes of safety, efficacy, and trust in institutions will need to be considered, as targeted outreach programs and intervention strategies are deployed on Twitter to improve the uptake of COVID-19 vaccination.

scholarly journals Analyzing Social Media to Explore the Attitudes and Behaviors Following the Announcement of Successful COVID-19 Vaccine Trials: Infodemiology Study (Preprint)

2021 ◽  
Author(s):  
Jean-Christophe Boucher ◽  
Kirsten Cornelson ◽  
Jamie L Benham ◽  
Madison M Fullerton ◽  
Theresa Tang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Content Analysis ◽  
Social Network ◽  
Multinational Corporations ◽  
Vaccine Hesitancy ◽  
Media Content ◽  
Media Content Analysis ◽  
Vaccine Trials ◽  
The Government

BACKGROUND The rollout of COVID-19 vaccines has brought vaccine hesitancy to the forefront in managing this pandemic. COVID-19 vaccine hesitancy is fundamentally different from that of other vaccines due to the new technologies being used, rapid development, and widespread global distribution. Attitudes on vaccines are largely driven by online information, particularly information on social media. The first step toward influencing attitudes about immunization is understanding the current patterns of communication that characterize the immunization debate on social media platforms. OBJECTIVE We aimed to evaluate societal attitudes, communication trends, and barriers to COVID-19 vaccine uptake through social media content analysis to inform communication strategies promoting vaccine acceptance. METHODS Social network analysis (SNA) and unsupervised machine learning were used to characterize COVID-19 vaccine content on Twitter globally. Tweets published in English and French were collected through the Twitter application programming interface between November 19 and 26, 2020, just following the announcement of initial COVID-19 vaccine trials. SNA was used to identify social media clusters expressing mistrustful opinions on COVID-19 vaccination. Based on the SNA results, an unsupervised machine learning approach to natural language processing using a sentence-level algorithm transfer function to detect semantic textual similarity was performed in order to identify the main themes of vaccine hesitancy. RESULTS The tweets (n=636,516) identified that the main themes driving the vaccine hesitancy conversation were concerns of safety, efficacy, and freedom, and mistrust in institutions (either the government or multinational corporations). A main theme was the safety and efficacy of mRNA technology and side effects. The conversation around efficacy was that vaccines were unlikely to completely rid the population of COVID-19, polymerase chain reaction testing is flawed, and there is no indication of long-term T-cell immunity for COVID-19. Nearly one-third (45,628/146,191, 31.2%) of the conversations on COVID-19 vaccine hesitancy clusters expressed concerns for freedom or mistrust of institutions (either the government or multinational corporations) and nearly a quarter (34,756/146,191, 23.8%) expressed criticism toward the government’s handling of the pandemic. CONCLUSIONS Social media content analysis combined with social network analysis provides insights into the themes of the vaccination conversation on Twitter. The themes of safety, efficacy, and trust in institutions will need to be considered, as targeted outreach programs and intervention strategies are deployed on Twitter to improve the uptake of COVID-19 vaccination.

scholarly journals Health Information Needs and Health Seeking Behavior during the 2014-2016 Ebola Outbreak: A Twitter Content Analysis

2017 ◽  
Author(s):  
Michelle L. Odlum ◽  
Sunmoo Yoon
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Health Information ◽  
Language Processing ◽  
Information Seeking ◽  
Information Needs ◽  
Disease Outbreaks ◽  
Time Data ◽  
Health Seeking ◽  
Over Time

AbstractIntroductionFor effective public communication during major disease outbreaks like the 2014-2016 Ebola epidemic, health information needs of the population must be adequately assessed. Through content analysis of social media data, like tweets, public health information needs can be effectively assessed and in turn provide appropriate health information to effectively address such needs. The aim of the current study was to assess health information needs about Ebola, at distinct epidemic time points, through longitudinal tracking.MethodsNatural language processing was applied to explore public response to Ebola over time from the beginning of the outbreak (July 2014) to six month post outbreak (March 2015). A total 155,647 tweets (unique 68,736, retweet 86,911) mentioning Ebola were analyzed and visualized with infographics.ResultsPublic fear, frustration, and health information seeking regarding Ebola-related global priorities were observed across time. Our longitudinal content analysis revealed that due to ongoing health information deficiencies, resulting in fear and frustration, social media was at times an impediment and not a vehicle to support health information needs.DiscussionContent analysis of tweets effectively assessed Ebola information needs. Our study also demonstrates the use of Twitter as a method for capturing real-time data to assess ongoing information needs, fear, and frustration over time.All authors have seen and approved the manuscript.

NEMO - The NEar real-time MOnitoring system for bright fireballs

2020 ◽  
Author(s):  
Theresa Ott ◽  
Esther Drolshagen ◽  
Detlef Koschny ◽  
Gerhard Drolshagen ◽  
Christoph Pilger ◽  
...  
Keyword(s):  
Social Media ◽  
Real Time ◽  
Monitoring System ◽  
European Space Agency ◽  
Data Sources ◽  
Real Time Monitoring ◽  
Space Agency ◽  
Safety Programme ◽  
Available Information ◽  
Test Ban

&lt;p&gt;Fireballs are very bright meteors with magnitudes of at least -4. They can spark a lot of public interest. Especially, if they can be seen&amp;#160;during daytime over populous areas. Social Media allows us to be informed about almost&amp;#160;everything,&amp;#160;worldwide, and&amp;#160;in all areas of life&amp;#160;in real-time. In the age of intensive use of these media, information is freely available seconds after the sighting of a fireball.&lt;/p&gt;&lt;p&gt;This is the basis of the alert system which is part of NEMO, the NEar real-time MOnitoring system,&amp;#160;for bright fireballs. It uses Social Media, mainly Twitter, to be informed about a fireball event in near real-time. In addition, the system accesses various data sources to collect further information about the detected fireballs. The sources range from meteor networks, the data from weather satellites or lightning detectors to the infrasound data of the IMS (International Monitoring System) operated by the CTBTO (Comprehensive Nuclear-Test-Ban Treaty Organisation).&lt;/p&gt;&lt;p&gt;Since large meteoroids or asteroids can be detected by these infrasound sensors when they enter the Earth's atmosphere, this network provides the possibility to detect fireballs worldwide and during day and night. From the infrasound data the energy of the object that caused the fireball can be determined and hence, its size and mass can be calculated. By combining all available information about the fireball from different data sources the amount of scientific knowledge about the event can be maximized.&lt;/p&gt;&lt;p&gt;NEMO was under development for about 2.5 years.&amp;#160;Since the beginning of the year the system is in operation at the European Space Agency, as part of its Space Safety Programme. In this presentation we will give an overview about NEMO, its working principle and its relation to the IMS.&lt;/p&gt;

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