Mask-related acne in the COVID-19 pandemic: an analysis of Twitter posts and influencers.
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ABSTRACT:
SUBMITTER: Drozdowski R
PROVIDER: S-EPMC8013391 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:IntroductionThe objective of this study was to analyze the messages of influential emergency medicine (EM) Twitter users in the United States (US) during the early stages of the coronavirus disease 2019 (COVID-19) global pandemic by characterizing the themes, emotional tones, temporal viewpoints, and depth of engagement with the tweets.MethodsWe performed a retrospective mixed-methods analysis of publicly available Twitter data derived from the publicly available "Coronavirus Tweet IDs" dataset, March 3, 2020-May 1, 2020. Original tweets and modified retweets in the dataset by 50 influential EM Twitter users in the US were analyzed using linguistic software to report the emotional tone and temporal viewpoint. We qualitatively analyzed a 25% random subsample and report themes.ResultsThere were 1315 tweets available in the dataset from 36/50 influential EM Twitter users in the US. The majority of tweets were either positive (455/1315, 34.6%) or neutral (407/1315, 31%) in tone and focused on the present (1009/1315, 76.7%). Qualitative analysis identified six distinct themes, with users most often sharing news or clinical information.ConclusionsDuring the early weeks of the COVID-19 pandemic, influential EM Twitter users in the US delivered mainly positive or neutral messages, most often pertaining to news stories or information directly relating to patient care. The majority of these messages led to engagement by other users. This study underscores how EM influencers can leverage social media in public health outbreaks to bring attention to topics of importance.
| S-EPMC8203008 | biostudies-literature
Project description:BackgroundAs vaping rapidly becomes more prevalent, social media data can be harnessed to capture individuals' discussions of e-cigarette products quickly. The JUUL vaporizer is the latest advancement in e-cigarette technology, which delivers nicotine to the user from a device that is the size and shape of a thumb drive. Despite JUUL's growing popularity, little research has been conducted on JUUL. Here we utilized Twitter data to determine the public's early experiences with JUUL describing topics of posts.MethodsTwitter posts containing the term "JUUL" were obtained for 1 April 2107 to 14 December 2017. Text classifiers were used to identify topics in posts (n = 81,689).ResultsThe most prevalent topic wasPerson Tagging (use of @username to tag someone in a post) at 20.48% followed by Pods (mentions of JUUL's refill cartridge) at 14.72% and Buying (mentions of purchases) at 10.49%. The topic School (posts indicative of using JUUL or seeing someone use JUUL while at elementary, middle, or high school) comprised 3.66% of posts. The topic of Quit Smoking was rare at 0.29%.ConclusionsData from social media may be used to extend the surveillance of newly introduced vaping products. Findings suggest Twitter users are bonding around, and inquiring about, JUUL on social media. JUUL's discreetness may facilitate its use in places where vaping is prohibited. Educators may be in need of training on how to identify JUUL in the classroom. Despite JUUL's branding as a smoking alternative, very few Twitter users mentioned smoking cessation with JUUL.
| S-EPMC6693487 | biostudies-literature
Project description:The COVID-19 pandemic has impacted all aspects of our lives, including the information spread on social media. Prior literature has found that information diffusion dynamics on social networks mirror that of a virus, but applying the epidemic Susceptible-Infected-Removed model (SIR) model to examine how information spread is not sufficient to claim that information spreads like a virus. In this study, we explore whether there are similarities in the simulated SIR model (SIRsim), observed SIR model based on actual COVID-19 cases (SIRemp), and observed information cascades on Twitter about the virus (INFOcas) by using network analysis and diffusion modeling. We propose three primary research questions: (a) What are the diffusion patterns of COVID-19 virus spread, based on SIRsim and SIRemp? (b) What are the diffusion patterns of information cascades on Twitter (INFOcas), with respect to retweets, quote tweets, and replies? and (c) What are the major differences in diffusion patterns between SIRsim, SIRemp, and INFOcas? Our study makes a contribution to the information sciences community by showing how epidemic modeling of virus and information diffusion analysis of online social media are distinct but interrelated concepts.
| S-EPMC7645904 | biostudies-literature
Project description:Introduction:E-liquid is the solution aerosolized by e-cigarette devices to produce vapor. Continuously evolving e-liquids, and corresponding devices, can affect user experiences associated with these products. Twitter conversations about e-liquids can capture salient behavioral, social, and communicative cues associated with e-liquids. We analyzed Twitter data to characterize key topics of conversation about e-liquids to inform surveillance, and regulatory efforts. Methods:Twitter posts containing e-liquid-related terms ("e-liquid(s)," "e-juice(s)") were obtained from 1 January 2018 to 31 December 2018. Text classifiers were used to identify topics of the posts (n?=?15,927). Results:The most prevalent topic was Promotional at 29.35% followed by Flavors at 24.22%, and Person Tagging at 21.47%. Juice Composition was next most prevalent at 17.61% followed by Cannabis at 16.83%, and Nicotine Health Risks at 6.39%. Quit Smoking was rare at 0.57%. Conclusion:These results suggest that flavors, cannabis, health risks of nicotine, and composition warrant consideration as targets in future surveillance, public policy, and interventions addressing the use of e-liquids. Twitter provides ample opportunity to influence the normalization, and uptake, of e-cigarette-related products among non-smokers and youth, unless regulatory restrictions, and counter messaging campaigns are developed to reduce this risk.
| S-EPMC6579902 | biostudies-literature
Project description:BackgroundWith the World Health Organization's pandemic declaration and government-initiated actions against coronavirus disease (COVID-19), sentiments surrounding COVID-19 have evolved rapidly.ObjectiveThis study aimed to examine worldwide trends of four emotions-fear, anger, sadness, and joy-and the narratives underlying those emotions during the COVID-19 pandemic.MethodsOver 20 million social media twitter posts made during the early phases of the COVID-19 outbreak from January 28 to April 9, 2020, were collected using "wuhan," "corona," "nCov," and "covid" as search keywords.ResultsPublic emotions shifted strongly from fear to anger over the course of the pandemic, while sadness and joy also surfaced. Findings from word clouds suggest that fears around shortages of COVID-19 tests and medical supplies became increasingly widespread discussion points. Anger shifted from xenophobia at the beginning of the pandemic to discourse around the stay-at-home notices. Sadness was highlighted by the topics of losing friends and family members, while topics related to joy included words of gratitude and good health.ConclusionsOverall, global COVID-19 sentiments have shown rapid evolutions within just the span of a few weeks. Findings suggest that emotion-driven collective issues around shared public distress experiences of the COVID-19 pandemic are developing and include large-scale social isolation and the loss of human lives. The steady rise of societal concerns indicated by negative emotions needs to be monitored and controlled by complementing regular crisis communication with strategic public health communication that aims to balance public psychological wellbeing.
| S-EPMC7247466 | biostudies-literature
Project description:BACKGROUND:Hookah (or tobacco waterpipe) use has recently become prevalent in the United States. The contexts and experiences associated with hookah use are unclear, yet such information is abundant via publicly available hookah users' social media postings. OBJECTIVE:In this study, we utilized Twitter data to characterize Twitter users' recent experiences with hookah. METHODS:Twitter posts containing the term "hookah" were obtained from April 1, 2017 to 29 March, 2018. Text classifiers were used to identify clusters of topics that tended to co-occur in posts (n=176,706). RESULTS:The most prevalent topic cluster was Person Tagging (use of @username to tag another Twitter account in a post) at 21.58% (38,137/176,706) followed by Promotional or Social Events (eg, mentions of ladies' nights, parties, etc) at 20.20% (35,701/176,706) and Appeal or Abuse Liability (eg, craving, enjoying hookah) at 18.12% (32,013/176,706). Additional topics included Hookah Use Behavior (eg, mentions of taking a "hit" of hookah) at 11.67% (20,603/176,706), Polysubstance Use (eg, hookah use along with other substances) at 10.95% (19,353/176,706), Buying or Selling (eg, buy, order, purchase, sell) at 9.37% (16,552/176,706), and Flavors (eg, mint, cinnamon, watermelon) at 1.66% (2927/176,706). The topic Dislike of Hookah (eg, hate, quit, dislike) was rare at 0.59% (1043/176,706). CONCLUSIONS:Social events, appeal or abuse liability, flavors, and polysubstance use were the common contexts and experiences associated with Twitter discussions about hookah in 2017-2018. Considered in concert with traditional data sources about hookah, these results suggest that social events, appeal or abuse liability, flavors, and polysubstance use warrant consideration as targets in future surveillance, policy making, and interventions addressing hookah.
| S-EPMC6277830 | biostudies-other
Project description:BackgroundSocial media plays a critical role in health communications, especially during global health emergencies such as the current COVID-19 pandemic. However, there is a lack of a universal analytical framework to extract, quantify, and compare content features in public discourse of emerging health issues on different social media platforms across a broad sociocultural spectrum.ObjectiveWe aimed to develop a novel and universal content feature extraction and analytical framework and contrast how content features differ with sociocultural background in discussions of the emerging COVID-19 global health crisis on major social media platforms.MethodsWe sampled the 1000 most shared viral Twitter and Sina Weibo posts regarding COVID-19, developed a comprehensive coding scheme to identify 77 potential features across six major categories (eg, clinical and epidemiological, countermeasures, politics and policy, responses), quantified feature values (0 or 1, indicating whether or not the content feature is mentioned in the post) in each viral post across social media platforms, and performed subsequent comparative analyses. Machine learning dimension reduction and clustering analysis were then applied to harness the power of social media data and provide more unbiased characterization of web-based health communications.ResultsThere were substantially different distributions, prevalence, and associations of content features in public discourse about the COVID-19 pandemic on the two social media platforms. Weibo users were more likely to focus on the disease itself and health aspects, while Twitter users engaged more about policy, politics, and other societal issues.ConclusionsWe extracted a rich set of content features from social media data to accurately characterize public discourse related to COVID-19 in different sociocultural backgrounds. In addition, this universal framework can be adopted to analyze social media discussions of other emerging health issues beyond the COVID-19 pandemic.
| S-EPMC7790734 | biostudies-literature
Project description:BackgroundLittle cigars are growing in popularity in the United States, and Swisher is the market leader. The contexts and experiences associated with the use of Swisher-related products is understudied, but such information is available via publicly available posts on Twitter.ObjectiveThis study aimed to analyze Twitter posts to characterize Twitter users' recent experiences with Swisher-related products.MethodsTwitter posts containing the term "swisher" were analyzed from January 1, 2018, to December 31, 2018. Text classifiers were used to identify topics in posts (n=81,333).ResultsThe most prevalent topic was Person Tagging (mentioning a Twitter account in a post; 32.77%), followed by Flavors (eg, Grape and Strawberry; 20.96%) and Swisher use (eg, smoke swisher; 17.44%). Additional topics included Cannabis use (eg, blunt, roll, and gut swisher; 6.26%), Appeal (eg, like Swisher; 5.92%), Dislike (eg, posts that showed dissatisfaction with Swisher products; 3.53%), Purchases (eg, buy swisher; 1.90%), and Cigar comparison (eg, mentions of other cigar products including White-owl and Backwoods; 1.64%).ConclusionsThis paper describes common contexts and experiences associated with the use of Swisher little cigars from the population posting on Twitter in 2018. These online messages may have offline consequences for tobacco-related behaviors, indicating the need for countering from public health officials. Findings should inform us about targets for surveillance, policy, and interventions addressing Swisher little cigars as well as communication planning and tobacco product counter messaging on Twitter.
| S-EPMC6676793 | biostudies-literature
Project description:AimTo investigate the experience of Italian nurses during the first wave of the COVID-19 outbreak by analysing professional social media posts.BackgroundThe COVID-19 outbreak has overwhelmed health care institutions; as a consequence, nurses' lives and psycho-physical health have been affected.IntroductionThe COVID-19 pandemic forced nurses to work in physically and psychologically stressful conditions impacting on their life.MethodsA qualitative descriptive study. All narratives (texts and videos) posted by nurses from the 23rd of February 2020 to the 3rd of May (from the start of the outbreak to the end of the first lockdown) were analysed and published on the five most popular Italian professional social media platforms. The Consolidated Criteria for Reporting Qualitative research guidelines were followed.ResultsFive themes emerged from the 380 narratives explored: 'Sharing what is happening within myself'; 'Experiencing unprecedented working conditions'; 'Experiencing a deep change'; 'Failing to rehabilitate the image of nurses in society'; and 'Do not abandon us'. Even though nurses appreciated the recognition of their communities, they still felt devalued and not recognized as professionals.DiscussionSeveral psychological, physical, social and professional implications emerged from nurses working during the COVID-19 pandemic. Despite being highly praised, nurses perceived they had failed in rehabilitating the image of nurses in society.ConclusionThe experience of working during the COVID-19 pandemic represented a traumatic event for nurses but it offered them personal and professional growth opportunities. IMPLICATIONS FOR NURSING PRACTICE, NURSING POLICY AND HEALTH POLICY: Supporting nurses' mental health is highly recommended, together with a cultural investment on nurses' role recognition, and a zero-tolerance policy towards violence and aggression towards nurses.
| S-EPMC8250969 | biostudies-literature
Project description:ObjectivesUsing Twitter, we aim to (1) define and quantify the prevalence and evolution of facets of social distancing during the COVID-19 pandemic in the US in a spatiotemporal context and (2) examine amplified tweets among social distancing facets.Materials and methodsWe analyzed English and US-based tweets containing "coronavirus" between January 23-March 24, 2020 using the Twitter API. Tweets containing keywords were grouped into six social distancing facets: implementation, purpose, social disruption, adaptation, positive emotions, and negative emotions.ResultsA total of 259,529 unique tweets were included in the analyses. Social distancing tweets became more prevalent from late January to March but were not geographically uniform. Early facets of social distancing appeared in Los Angeles, San Francisco, and Seattle: the first cities impacted by the COVID-19 outbreak. Tweets related to the "implementation" and "negative emotions" facets largely dominated in combination with topics of "social disruption" and "adaptation", albeit to lesser degree. Social disruptiveness tweets were most retweeted, and implementation tweets were most favorited.DiscussionSocial distancing can be defined by facets that respond to and represent certain events in a pandemic, including travel restrictions and rising case counts. For example, Miami had a low volume of social distancing tweets but grew in March corresponding with the rise of COVID-19 cases.ConclusionThe evolution of social distancing facets on Twitter reflects actual events and may signal potential disease hotspots. Our facets can also be used to understand public discourse on social distancing which may inform future public health measures.
| S-EPMC7553881 | biostudies-literature