scholarly journals Antivaccine Movement and COVID-19 Negationism: A Content Analysis of Spanish-Written Messages on Twitter

Vaccines ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 656
Author(s):  
Ivan Herrera-Peco ◽  
Beatriz Jiménez-Gómez ◽  
Carlos Santiago Romero Magdalena ◽  
Juan José Deudero ◽  
María García-Puente ◽  
...  
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Genetic Code ◽  
Great Influence ◽  
Vaccine Safety ◽  
Communication Strategy ◽  
Health Organizations ◽  
Twitter Data ◽  
Influential Users ◽  
Main Language

During the COVID-19 pandemic, different conspiracies have risen, with the most dangerous being those focusing on vaccines. Today, there exists a social media movement focused on destroying the credibility of vaccines and trying to convince people to ignore the advice of governments and health organizations on vaccination. Our aim was to analyze a COVID-19 antivaccination message campaign on Twitter that uses Spanish as the main language, to find the key elements in their communication strategy. Twitter data were retrieved from 14 to 28 December using NodeXL software. We analyzed tweets in Spanish, focusing on influential users, most influential tweets, and content analysis of tweets. The results revealed ordinary citizens who ‘offer the truth’ as the most important profile in this network. The content analysis showed antivaccine tweets (31.05%) as the most frequent. The analysis of anti-COVID19 tweets showed that attacks against vaccine safety were the most important (79.87%) but we detected a new kind of message presenting the vaccine as a means of manipulating the human genetic code (8.1%). We concluded that the antivaccine movement and its tenets have great influence in the COVID-19 negationist movement. We observed a new topic in COVID-19 vaccine hoaxes that must be considered in our fight against misinformation.

scholarly journals Adapting and Extending a Typology to Identify Vaccine Misinformation on Twitter

2020 ◽  
Vol 110 (S3) ◽  
pp. S331-S339
Author(s):  
Amelia Jamison ◽  
David A. Broniatowski ◽  
Michael C. Smith ◽  
Kajal S. Parikh ◽  
Adeena Malik ◽  
...  
Keyword(s):  
Machine Learning ◽  
Content Analysis ◽  
Topic Modeling ◽  
Latent Dirichlet Allocation ◽  
Vaccine Safety ◽  
Manual Annotation ◽  
Information Communication ◽  
Data Set ◽  
Machine Learning Methods ◽  
Twitter Data

Objectives. To adapt and extend an existing typology of vaccine misinformation to classify the major topics of discussion across the total vaccine discourse on Twitter. Methods. Using 1.8 million vaccine-relevant tweets compiled from 2014 to 2017, we adapted an existing typology to Twitter data, first in a manual content analysis and then using latent Dirichlet allocation (LDA) topic modeling to extract 100 topics from the data set. Results. Manual annotation identified 22% of the data set as antivaccine, of which safety concerns and conspiracies were the most common themes. Seventeen percent of content was identified as provaccine, with roughly equal proportions of vaccine promotion, criticizing antivaccine beliefs, and vaccine safety and effectiveness. Of the 100 LDA topics, 48 contained provaccine sentiment and 28 contained antivaccine sentiment, with 9 containing both. Conclusions. Our updated typology successfully combines manual annotation with machine-learning methods to estimate the distribution of vaccine arguments, with greater detail on the most distinctive topics of discussion. With this information, communication efforts can be developed to better promote vaccines and avoid amplifying antivaccine rhetoric on Twitter.

scholarly journals COVID-19 and the 5G Conspiracy Theory: Social Network Analysis of Twitter Data

10.2196/19458 ◽  
2020 ◽  
Vol 22 (5) ◽  
pp. e19458 ◽  
Author(s):  
Wasim Ahmed ◽  
Josep Vidal-Alaball ◽  
Joseph Downing ◽  
Francesc López Seguí
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
United Kingdom ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Conspiracy Theory ◽  
Fake News ◽  
The United Kingdom ◽  
Twitter Data

Background Since the beginning of December 2019, the coronavirus disease (COVID-19) has spread rapidly around the world, which has led to increased discussions across online platforms. These conversations have also included various conspiracies shared by social media users. Amongst them, a popular theory has linked 5G to the spread of COVID-19, leading to misinformation and the burning of 5G towers in the United Kingdom. The understanding of the drivers of fake news and quick policies oriented to isolate and rebate misinformation are keys to combating it. Objective The aim of this study is to develop an understanding of the drivers of the 5G COVID-19 conspiracy theory and strategies to deal with such misinformation. Methods This paper performs a social network analysis and content analysis of Twitter data from a 7-day period (Friday, March 27, 2020, to Saturday, April 4, 2020) in which the #5GCoronavirus hashtag was trending on Twitter in the United Kingdom. Influential users were analyzed through social network graph clusters. The size of the nodes were ranked by their betweenness centrality score, and the graph’s vertices were grouped by cluster using the Clauset-Newman-Moore algorithm. The topics and web sources used were also examined. Results Social network analysis identified that the two largest network structures consisted of an isolates group and a broadcast group. The analysis also revealed that there was a lack of an authority figure who was actively combating such misinformation. Content analysis revealed that, of 233 sample tweets, 34.8% (n=81) contained views that 5G and COVID-19 were linked, 32.2% (n=75) denounced the conspiracy theory, and 33.0% (n=77) were general tweets not expressing any personal views or opinions. Thus, 65.2% (n=152) of tweets derived from nonconspiracy theory supporters, which suggests that, although the topic attracted high volume, only a handful of users genuinely believed the conspiracy. This paper also shows that fake news websites were the most popular web source shared by users; although, YouTube videos were also shared. The study also identified an account whose sole aim was to spread the conspiracy theory on Twitter. Conclusions The combination of quick and targeted interventions oriented to delegitimize the sources of fake information is key to reducing their impact. Those users voicing their views against the conspiracy theory, link baiting, or sharing humorous tweets inadvertently raised the profile of the topic, suggesting that policymakers should insist in the efforts of isolating opinions that are based on fake news. Many social media platforms provide users with the ability to report inappropriate content, which should be used. This study is the first to analyze the 5G conspiracy theory in the context of COVID-19 on Twitter offering practical guidance to health authorities in how, in the context of a pandemic, rumors may be combated in the future.

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 The Structure of Tweets about Vaccine Safety Between Health Organizations, Experts and the Public: Analyzing Risk Communication Conversations

2020 ◽  
pp. 1-25
Author(s):  
David Manheim ◽  
Anat Gesser-Edelsburg
Keyword(s):  
Social Media ◽  
Best Practices ◽  
Risk Communication ◽  
Vaccine Safety ◽  
World Health ◽  
Structure Theory ◽  
Health Organizations ◽  
The Public ◽  
The World ◽  
Conversational Structure

Abstract This paper considers how health education organizations in the World Health Organization's Vaccine Safety Network (VSN) use Twitter to communicate about vaccines with the public, and whether they answer questions and engage in conversations. Almost no research in public health, to our knowledge, has explored conversational structure on social media among posts sent by different accounts. Starting with 1,017,176 tweets by relevant users, we constructed two corpuses of multi-tweet conversations. The first was 1,814 conversations that included VSN members directly, while the second was 2,283 conversations mentioning vaccines or vaccine denialism. The tweets and user metadata was then analyzed using an adaptation of Rhetorical Structure Theory. In the studied data, VSN members tweeted 12,677 times within conversations, compared to their 37,587 lone tweets. Their conversations were shorter than those in the comparison corpus (P < 0.0001), and they were involved in fewer multilogues (P < 0.0001). We also see that while there is diversity among organizations, most were tied to the pre-social-media broadcast model. In the future, they should try to converse more, rather than tweet more, and embrace best-practices in risk-communication.

Framing the Global Youth Climate Movement: A Qualitative Content Analysis of Greta Thunberg’s Moral, Hopeful, and Motivational Framing on Instagram

2021 ◽  
pp. 194016122110556
Author(s):  
Amanda L. Molder ◽  
Alexandra Lakind ◽  
Zoe E. Clemmons ◽  
Kaiping Chen
Keyword(s):  
Climate Change ◽  
Social Media ◽  
Content Analysis ◽  
Qualitative Content Analysis ◽  
Communication Strategy ◽  
Future Generations ◽  
First Year ◽  
Unique Case ◽  
Emotional Appeal ◽  
Social Media Platforms

Climate change is a critical global problem that requires immediate action to mitigate its effects. In recent years, youth climate activists have mobilized worldwide protests to demand action, using social media platforms to communicate and broadcast their message. This study examines Greta Thunberg's rise to global prominence through an analysis of her first year and a half of Instagram posts from June 2018 to January 2020, including visual and textual elements. First, we explore how climate change is communicated on social media by youth activists, and then examine these concepts through the unique case of Thunberg’s Instagram. Then, through qualitative content analysis, this study elucidates her communication strategy by applying the concept of framing to unpack how she frames climate change as a moral and ethical issue, uses an emotional appeal of hope, and visually frames motivational collective action to mobilize her audience. Finally, we discuss the implications of our findings to explore the complexities of communicating climate change through social media and how Thunberg's activism on Instagram may provide an example for future generations.

Character assassination as a right-wing populist communication tactic on social media: The case of Matteo Salvini in Italy

2021 ◽  
pp. 146144482110392
Author(s):  
Carlo Berti ◽  
Enzo Loner
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
Qualitative Analysis ◽  
Communication Strategy ◽  
Right Wing ◽  
Media Communication ◽  
The People ◽  
Individual Traits ◽  
Social Media Communication

The article conceptualizes character assassination (CA) as a tactic of populist communication on social media by using the case study of Italian politician Matteo Salvini. CA consists of personal attacks aimed at damaging the reputation of individuals, used as political means to attack the “enemies of the people.” By means of CA, populists operate a shift from issues and arguments toward individual traits and behaviors. CA’s importance is linked to the features of social media communication (i.e. disintermediation, speed, virality, fragmentation, emotionality). The article uses content analysis of tweets, and qualitative analysis of relevant examples; it demonstrates the strategic nature of CA in Salvini’s communication and identifies five functions (i.e. polarizing, personalizing, symbolic, discriminating, emotional) of CA in right-wing populist communication. CA’s logic is unpacked, by showing how the delegitimization of individuals is used to reinforce a populist communication strategy. Potential implications and responses to CA are discussed.

Characterising “Green Building” as a topic in Twitter

2019 ◽  
Vol 19 (4) ◽  
pp. 513-530
Author(s):  
Stuart Palmer ◽  
Nilupa Udawatta
Keyword(s):  
Social Media ◽  
Green Building ◽  
Building Construction ◽  
Sustainable Construction ◽  
Large Set ◽  
Data Set ◽  
Content Type ◽  
Twitter Data ◽  
Influential Users ◽  
Twitter Activity

PurposeSustainable construction is widely considered to be the best practice in construction, helping to create a healthy built environment. Social media is identified as a valuable data source for research on sustainable construction, and Twitter is a popular social media platform in relation to the construction. Green Building construction is identified as one of the methods that promotes sustainable construction. The purpose of this study is to characterise “Green Building” as a topic in Twitter.Design/methodology/approachSocial network analysis methods were applied to a large set of Twitter data related to “green building”. Time sequence analysis and network visualisation were used to characterise Twitter activity and to identify influential users. Text analytics and visualisation methods were applied to the same data set to visualise the text content of Twitter posts relating to green building.FindingsPeaks in Twitter activity were associated with physical “green building” events. The network visualisation of the Twitter data revealed a complex structure and a range of types of interactions. The most “influential” users depended on the ranking method used; however, a number of users had high influence in all measures used. The tweet text visualisation showed evidence of a global and interactive audience on Twitter engaged in conversations about green building. Also, it was found that external links, emoji and popular terms related to a particular topic can be used to increase the engagement of Twitter users on that topic.Originality/valueCertain Green Building events were observed to be associated with high levels of Twitter activity. The virtual was found to be closely linked to the physical, and for the promotion of green building construction, their respective impact is potentially the most powerful when used in conjunction. The most influential Twitter accounts did not belong to one class of user, including both individuals and organisations. Twitter offers a platform for a range of stakeholders in the area of green building construction to reach a substantial audience and to be influential in the public sphere. The findings of this research provide a valuable reference for industry practitioners and researchers to deepen their understanding of the application of Twitter to green building construction, and the methods of using Twitter to promote important information related to sustainable construction.

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 Tracking Gauteng thunderstorms using Crowdsourced Twitter data between Soweto and Pretoria

2014 ◽  
Vol 10 (3) ◽  
Author(s):  
Laurie Butgereit
Keyword(s):  
Social Media ◽  
Content Analysis ◽  
South African ◽  
Lightning Stroke ◽  
Populated Area ◽  
Textual Information ◽  
Geographical Data ◽  
Analysis Techniques ◽  
Twitter Data ◽  
Crowdsourced Data

Summer thunderstorms in Gauteng are often dramatic, noisy, wet events. They can appear suddenly on exceptionally hot sunny days travelling fast across the province. With such dramatic arrivals, people often flock to social media sites such as Twitter to comment on the rain, wind, hail, lightning and thunder. This paper investigates the possibility of mapping the track of Gauteng thunderstorms by using crowdsourced data from Twitter. This paper describes a model (entitled the ThunderChatter Model) and instantiation of that model which extracts data from Twitter, analyses the textual information for thunderstorm information and plots the appropriate data on a map. For evaluation purposes, these generated maps are then compared against lightning-stroke maps provided by the South African Weather Service. The maps are visually compared by independent people using Content Analysis techniques ensuring unbiased and reproducible results. The results of this research are mixed. For thunderstorms which traverse the strip of land between Soweto and Pretoria more or less correlated to the N1 highway (and representing the most heavily populated area of Gauteng and the area with the highest percentage of home Internet facilities), the results are excellent. However, in outlying areas of Gauteng such as Carletonville, Heidelberg, Hammanskraal and Bronkhorstspruit, the thunderstorms are only trackable using crowdsourced Twitter data in the case of extreme storms which damage property. The results imply that data obtained from social media could be used in some cases to supplement geographical data obtained from traditional sources.

Sign in / Sign up

Export Citation Format

Share Document