Twitter jako źródło wiedzy o stanie zdrowia polskiego społeczeństwa – ujęcie infodemiologiczne.

2017 ◽  
Vol 3 (49) ◽  
pp. 120-0
Author(s):  
Agata Malesińska

Article explores a novel concept of mining social media for information on public health (infodemiology) and provides insight into chosen results of original research covering random tweets by Polish Twitter users. Author asks what public health information can be learned from “Polish Twitter” and whether the collected data might be a valuable and reliable starting point for a broader analysis of Polish public health.

2020 ◽  
pp. 1329878X2095815
Author(s):  
Catherine Archer ◽  
Katharina Wolf ◽  
Joseph Nalloor

This article examines the role of influencers during the early stages of the COVID-19 pandemic, as well as the impact of the global pandemic on Social Media Influencers’ (SMIs) lifestyle and business model, using the concept of Disaster Capitalism as a springboard for discussion. Worldwide it first appeared that the global pandemic would severely impact SMI sole traders, as income from travel, luxury goods and other ‘lifestyle’ brands dried up. However, we suggest that brands and influencers themselves have pivoted to meet the COVID challenge, with some brands exploiting the opaque influence of these micro-celebrities. We further suggest that while a handful of governments and health organisations have recognised the reach and social capital of SMIs, their potential in health communication has been underutilised. We write this essay as a starting point, raising questions and calling for further research to be conducted to inform the understanding of SMIs’ role and potential as conveyors of public health information.


2020 ◽  
pp. 152483991989992
Author(s):  
Jordan L. Nelon ◽  
Michael Moscarelli ◽  
Payton Stupka ◽  
Christina Sumners ◽  
Taylor Uselton ◽  
...  

In the early 2000s, there was a shift in the use of the internet. Individuals on the internet began seeking information from other creators and creating their own content. These online communities allowed individuals to communicate across the globe, gravitating toward people like them or those who shared similar beliefs. Conversations around vaccinations have been particularly polarizing across social media even though scientific literature continually validates their safety and effectiveness. This study will explore whether online public discourse about vaccinations changes before and after major scientific publications, and will measure what is related to social engagement around vaccinations on Twitter. In September 2018, two weeks’ worth of Twitter posts ( n = 2,919) discussing vaccinations were collected, coded, and analyzed before and after two major 2014 scientific publications. Linear regression analyses examined variables related to engagement with vaccination-related Tweets pre- and postpublication. Antivaccine-related Tweets decreased by over 25% after scientific publications, while provaccine Tweets increased by 16.6%. Regression models suggest verification status and number of followers were the strongest predictors of Twitter engagement. Findings indicate that scientific publications might affect what people public health information people share online, and how people engage with online content. In a time when false information is easily spread online, this study suggests the need for continual scientific publication on “hot topics,” and urges researchers to partner with influential individuals on social media to disseminate effective, evidence-based, and user-friendly public health information to the public.


2021 ◽  
Vol 7 (2) ◽  
pp. 205630512110249
Author(s):  
Ryan J. Gallagher ◽  
Larissa Doroshenko ◽  
Sarah Shugars ◽  
David Lazer ◽  
Brooke Foucault Welles

In the absence of clear, consistent guidelines about the COVID-19 pandemic in the United States, many people use social media to learn about the virus, public health directives, vaccine distribution, and other health information. As people individually sift through a flood of information online, they collectively curate a small set of accounts, known as crowdsourced elites, that receive disproportionate attention for their COVID-19 content. However, these elites are not all created equal: not all accounts have received the same attention during the pandemic, and various demographic and ideological groups have crowdsourced their own elites. Using a mixed-methods approach with a panel of Twitter users in the United States over the first year of the COVID-19 pandemic, we identify COVID-19 crowdsourced elites. We distinguish sustained amplification from episodic amplification and demonstrate that crowdsourced elites vary across demographics with respect to race, geography, and political alignment. Specifically, we show that different subpopulations preferentially amplify elites that are demographically similar to them, and that they crowdsource different types of elite accounts, such as journalists, elected officials, and medical professionals, in different proportions. In light of this variation, we discuss the potential for using the disproportionate online voice of crowdsourced COVID-19 elites to equitably promote public health information and mitigate misinformation across networked publics.


Rheumatology ◽  
2018 ◽  
Vol 57 (suppl_3) ◽  
Author(s):  
Elizabeth Heron ◽  
Amy Curran ◽  
Osman H Ahmed ◽  
Jem Lawson ◽  
Lara Chapman ◽  
...  

2021 ◽  
Author(s):  
Hannah Stevens ◽  
Nicholas A. Palomares

BACKGROUND Amidst the widespread global COVID-19 pandemic, social media have played a pivotal role in the circulation of health information. Public health agencies often use Twitter as a tool to disseminate and amplify the propagation of such information [1], but exposure to local government-endorsed COVID-19 public health information does not make one immune to believing in misinformation. Moreover, not all health information on Twitter is accurate, and some users may believe misinformation and disinformation just as much as those who endorse more accurate information [2]. This situation is complicated when considering the unfortunate reality that elected officials may be promoting misinformation in pursuit of their other political agendas, like downplaying the need for COVID-19 restrictions to promote their reelection bid [3]. The politicized and polarized nature of information surrounding COVID-19 on social media in the U.S. has fueled a concomitant COVID-19 social media infodemic [4-6]. As such, because pre-existing political beliefs can both facilitate and hinder persuasion [7,8], goal understanding processes are likely at work in the belief of COVID-19 misinformation for Twitter users, such that the valence of users’ goal inferences for their local government agencies likely impact the extent to which they believe state government-endorsed COVID-19 information disseminated via social media. OBJECTIVE The present investigation sheds light on the cognitive processes of goal understanding that underlie the relationship between partisanship and belief in health misinformation. We investigate how Twitter users’ goal inference valence of local government’s COVID-19 efforts predicts their beliefs in COVID-19 misinformation as a function of their political party. METHODS We conducted an online cross-sectional survey of U.S. Twitter users who followed their state’s official department of public health Twitter (n=258) between August 10 and December 23, 2020. Local government goal inferences, demographics, and COVID-19 misinformation were measured. State political affiliation was controlled. RESULTS Participants from all 50 states were in the sample. Results revealed an interaction between political party affiliation and goal inference valence on belief in covid misinformation, R2∆ = .04, F(8,249) = 4.78, p < .001, such that positive goal inference valence predicted increased belief in COVID-19 misinformation for Republicans, β=.47, t(249) = 2.59, p = 0.01 but not Democrats, β= .07, t(249) = 0.84, p = 0.40. CONCLUSIONS Results reveal that positive inferences about local government’s COVID-19 efforts can accelerate beliefs in misinformation for Republican-identifying constituents. Republicans’ inferences that their local government has positive intentions may make republican constituents more vulnerable to republican-endorsed COVID-19 misinformation. In other words, accurate COVID-19 transmission knowledge has been driven by constituents' sentiment about politicians rather than science. This work stresses the need for health campaigns to be sensitive to the preexisting political affiliation of their target audience when constructing persuasive health messages.


2020 ◽  
Author(s):  
Takeo Yasu

BACKGROUND Serious public health problems, such as the COVID-19 pandemic, can cause an infodemic. Sources of information that may cause an infodemic include social networking services; YouTube, which consists of content created and uploaded by individuals, is one such source. OBJECTIVE To survey the content and changes in YouTube videos that present public health information about COVID-19 in Japan. METHODS We surveyed YouTube content regarding public health information pertaining to COVID-19 in Japan. YouTube searches were performed on March 6, 2020 (before the state of emergency), April 14 (during the state of emergency), and May 27 (after the state of emergency was lifted), with 136, 113, and 140 sample videos evaluated, respectively. The main outcome measures were: (1) The total number of views for each video, (2) video content, and (3) the usefulness of the video. RESULTS In the 100 most viewed YouTube videos during the three periods, the number of videos on public health information in March was significantly higher than in May (p = .02). Of the 331 unique videos, 9.1% (n = 30) were released by healthcare professionals. Useful videos providing public health information about the prevention of the spread of infection comprised only 13.0% of the sample but were viewed significantly more often than not useful videos (p = .006). CONCLUSIONS Individuals need to take care when obtaining information from YouTube before or early in a pandemic, during which time scientific evidence is scarce.


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