Regional insights on tobacco-related tweets: unveiling user opinions and usage patterns.

Introduction: Tobacco consumption and its impact on health remain high worldwide. Additionally, it is a contentious issue generating significant controversy. Twitter has proven to be a useful platform for evaluating public health topics related to population health behaviors, and tobacco consumption. Objective: The objective of this study is to analyze the content of tweets related to tobacco. Moreover, geolocation data will be considered to understand regional differences. Methods: Tweets published between 2018 and 2022, in both English and Spanish, containing the keyword "tobacco," were analyzed. A total of 56,926 tweets were obtained. The tweets were classified into different categories. 550 tweets were manually analyzed, and an automated and computerized classification was performed for the remaining and largest subset of tweets. Results: The analysis yielded 30,812 classifiable tweets. Healthcare professionals were the most frequent contributors to the topic (50.2%), with the most common theme being general information about the toxic effects of tobacco. 57.9% of the tweets discussed the harmful effects of tobacco on health, with fear being the predominant emotion. The largest number of tweets were located in America. Conclusions: Our study revealed a substantial number of tweets highlighting the health risks and negative perceptions of tobacco consumption. Africa showed the lowest percentage of tweets discussing the health risks associated with tobacco, coinciding with the continent having the least developed anti-tobacco policies. Healthcare professionals emerged as the most prominent users discussing the topic, which is encouraging as they play a crucial role in disseminating accurate and scientific health information.

Exploring Twitter chatter to assess the type and availability of cannabis-related products in Thailand.

Cannabis-related tweets were collected between January and April 2022 to estimate the availability and characteristics of cannabis products advertised on Twitter amid the legalization of recreational cannabis in Thailand. The Twitter API was called using the tweepy Python library to collect cannabis-related tweets in the Thai language. A total of 185,558 unique tweets were collected over the duration of the data collection period based on 83 search terms. Twenty thousand random tweets were manually coded by four Thai native speakers to assess the volume and characteristics of tweets proposing cannabis. 72.6% of collected tweets from the 20,000 random samples were coded as relevant to the study. 54.6% of relevant tweets were advertising cannabis products, 29.8% were personal communications, and 15.6% were related to news or media content. Among the tweets that advertised cannabis products, 94.4% proposed cannabis flower, 2.4% cannabis edibles and 1.8% cannabis concentrates. Consumption of potent forms of cannabis such as cannabis edibles and concentrates increase the risk of harmful side-effects, especially in a population with limited knowledge about these products. Our findings call for additional monitoring efforts and for increasing the public awareness on potent cannabis products emerging in Thailand.

High economic inequality is linked to greater moralization.

Throughout the 21st century, economic inequality is predicted to increase as we face new challenges, from changes in the technological landscape to the growing climate crisis. It is crucial we understand how these changes in inequality may affect how people think and behave. We propose that economic inequality threatens the social fabric of society, in turn increasing moralization-that is, the greater tendency to employ or emphasize morality in everyday life-as an attempt to restore order and control. Using longitudinal data from X, formerly known as Twitter, our first study demonstrates that high economic inequality is associated with greater use of moral language online (e.g. the use of words such as "disgust", "hurt", and "respect'). Study 2 then examined data from 41 regions around the world, generally showing that higher inequality has a small association with harsher moral judgments of people's everyday actions. Together these findings demonstrate that economic inequality is linked to the tendency to see the world through a moral lens.

Public Perceptions and Discussions of the US Food and Drug Administration's JUUL Ban Policy on Twitter: Observational Study.

BACKGROUND: On June 23, 2022, the US Food and Drug Administration announced a JUUL ban policy, to ban all vaping and electronic cigarette products sold by Juul Labs. OBJECTIVE: This study aims to understand public perceptions and discussions of this policy using Twitter (subsequently rebranded as X) data. METHODS: Using the Twitter streaming application programming interface, 17,007 tweets potentially related to the JUUL ban policy were collected between June 22, 2022, and July 25, 2022. Based on 2600 hand-coded tweets, a deep learning model (RoBERTa) was trained to classify all tweets into propolicy, antipolicy, neutral, and irrelevant categories. A deep learning model (M3 model) was used to estimate basic demographics (such as age and gender) of Twitter users. Furthermore, major topics were identified using latent Dirichlet allocation modeling. A logistic regression model was used to examine the association of different Twitter users with their attitudes toward the policy. RESULTS: Among 10,480 tweets related to the JUUL ban policy, there were similar proportions of propolicy and antipolicy tweets (n=2777, 26.5% vs n=2666, 25.44%). Major propolicy topics included "JUUL causes youth addition," "market surge of JUUL," and "health effects of JUUL." In contrast, major antipolicy topics included "cigarette should be banned instead of JUUL," "against the irrational policy," and "emotional catharsis." Twitter users older than 29 years were more likely to be propolicy (have a positive attitude toward the JUUL ban policy) than those younger than 29 years. CONCLUSIONS: Our study showed that the public showed different responses to the JUUL ban policy, which varies depending on the demographic characteristics of Twitter users. Our findings could provide valuable information to the Food and Drug Administration for future electronic cigarette and other tobacco product regulations.

Tweeting environmental pollution: Analyzing twitter language to uncover its correlation with county-level obesity rates in the United States.

BACKGROUND: Environmental pollution has been linked to obesogenic tendencies. Using environmental-related posts from Twitter (now known as X) from U.S. counties, we aim to uncover the association between Twitter linguistic data and U.S. county-level obesity rates. METHODS: Analyzing nearly 300 thousand tweets from January 2020 to December 2020 across 207 U.S. counties, using an innovative Differential Language Analysis technique and drawing county-level obesity data from the 2020 Food Environment Atlas to identify distinct linguistic features in Twitter relating to environmental-related posts correlated with socioeconomic status (SES) index indicators, obesity rates, and obesity rates controlled for SES index indicators. We also employed predictive modeling to estimate Twitter language's predictive capacity for obesity rates. RESULTS: Results revealed a negative correlation between environmental-related tweets and obesity rates, both before and after adjusting for SES. Contrarily, non-environmental-related tweets showed a positive association with higher county-level obesity rates, indicating that individuals living in counties with lower obesity rates tend to tweet environmental-related language more frequently than those living in counties with higher obesity rates. The findings suggest that linguistic patterns and expressions employed in discussing environmental-related themes on Twitter can offer unique insights into the prevailing cross-sectional patterns of obesity rates. CONCLUSIONS: Although Twitter users are a subset of the general population, incorporating environmental-related tweets and county-level obesity rates and using a novel language analysis technique make this study unique. Our results indicated that Twitter users engaging in more active dialog about environmental concerns might exhibit healthier lifestyle practices, contributing to reduced obesity rates.

Work-life balance Twitter insights: A social media analysis before and after COVID-19 pandemic.

This research examines the perceptions of Twitter users regarding the prevalent topics within Work-Life Balance communication before and after the COVID-19 pandemic. The pressing questions surrounding current labour market drivers are addressed, particularly regarding the ongoing Fourth Industrial Revolution and the COVID-19 pandemic's impact on communicated themes, particularly in the Human Resource Management field, where Work-Life Balance has emerged as a key concept. Social media platforms like Twitter are pivotal in fostering discussions on Work-Life Balance in society. Over the past decade, Twitter has evolved into a significant research platform researchers utilise in more than ten thousand research articles. The online discourse on Twitter raises awareness of the importance of balancing work and personal life. The COVID-19 pandemic has unveiled new facets of Work-Life Balance, with social media as a key platform for discussing these issues. This research uses Social Media Analysis based on the Hashtag Research framework. A total of 1,768,628 tweets from 499,574 users were examined, and frequency, topic, and sentiment analysis were conducted. Pre-pandemic, the most communicated Work-Life Balance topics were performance and time management, while recruitment and employee development were identified post-pandemic. Pre-pandemic, the highest proportion of negative sentiment was time management and mental health prevention, shifting to time, employee development, and mental health prevention post-pandemic. Despite the limitations of our research, a proposed redefinition of the concept is also presented, including a design for an integrated Work-Life Balance model based on topics communicated by Twitter users. Given the need for a more robust approach to redefining the concept and developing an integrative Work-Life Balance model, the article provides fresh insights for future research.

In-party love spreads more efficiently than out-party hate in online communities.

In this article, we present the findings of a comprehensive longitudinal social network analysis conducted on Twitter across four consecutive election campaigns in Spain, spanning from 2015 to 2019. Our focus is on the discernible trend of increasing partisan and ideological homogeneity within interpersonal exchanges on this social media platform, alongside high levels of networking efficiency measured through average retweeting. This diachronic study allows us to observe how dynamics of party competition might contribute to perpetuating and strengthening network ideological and partisan homophily, creating 'epistemic bubbles' in Twitter, yet showing a greater resistance to transforming them into 'partisan echo-chambers.' Specifically, our analysis reveals that the rise of a new radical right-wing party (RRP), Vox, has heightened ideological homogeneity among users across the entire ideological spectrum. However, this process has not been uniform. While users aligned with mainstream political parties consistently share content that reinforces in-party affinity, resulting in highly efficient 'epistemic bubbles,' the emergence of the RRP has given rise to a distinct group of users associated with the most extreme partisan positions, characterized by a notable proportion of out-partisan hostility content, which has fostered the creation of low-efficient 'partisan echo-chambers.'

Neurosurgery Residency Programs on Twitter (X): Current Use and Future Potential.

STUDY DESIGN: Cross-sectional study OBJECTIVES: Twitter (X) is increasingly utilized by medical residency programs to boost engagement and potentially enhance ranking. This study aims to evaluate the role of Twitter (X) in neurosurgery residency programs, assessing their online activity, followership, and content to identify current practices and potential improvements. METHODS: We identified 97/123 neurosurgery residency programs in the United States with Twitter accounts. Active accounts, posting in 2022 and 2023, were matched with the American Association of Neurological Surgeons (AANS) Neurosurgical Residency Training Program Directory. Tweets from January 2022 through June 2023 were categorized as original or retweets and further subcategorized based on content. Descriptive and correlation analyses were conducted. RESULTS: Twitter (X) accounts were found for 78.8% of accredited neurosurgery programs (n=97/123), with 68.3% active as of July 2023 (n=84/123). All active accounts amassed 167,068 followers. Among 5,612 tweets identified, 2,764 were original content and 2,848 were retweets. Tweets primarily focused on resident or program information (64.3%), research publications (32.0%), and conference participation (9.4%). Only 12.3% (n=341) of original tweets contained public medical information. A significant correlation (r = 0.493, p <0.001) was observed between Twitter (X) following and program ranking. CONCLUSIONS: The majority of US neurosurgery residency programs actively use Twitter (X), primarily to showcase academic achievements and aid in recruitment. The correlation between Twitter following and program ranking suggests that online engagement reflects program visibility and impact, underscoring the importance of social media in program outreach and strategic management for maximizing program benefits.

"This was never about a virus": Perceptions of Vaccination Hazards and Pandemic Risk in #Covid19NZ Tweets.

In this paper, we draw on qualitative methods from the medical humanities and quantitative approaches from corpus linguistics to assess the different mappings of pandemic risks by Twitter (X) users employing the #Covid19nz hashtag. We look specifically at their responses to government measures around vaccines between August and November 2021. Risk, we reveal, was a major discursive thread in tweets during this period, but within our tweets, it was the vaccine rather than the virus around which hazard perception and response were grouped. We find that the discursive stance of those opposed to the vaccine evoked entangled medical and political hazards, untrustworthy experts, obscure information, restrictions on sovereignty, threats to children, and uncertain future dangers, all of which positioned them within what Ulrich Beck termed the world risk society. We also found that these narratives of risk manifested in specific Twitter styles, which employed a consistently larger number of hashtags. The lack of conjunctions between the hashtags, we argue, encouraged a disordered reading of doubt and precaution, as the hashtags presented triggering phrases whose interconnections were hinted at rather than specified. By contrast, those who tweeted in support of government measures were rhetorically led by solutions rather than risks, with one exception: their perception of those who were vaccine opposed. We use scholarship on risk and precautionary logic to map out the contrasting positions in tweets addressing Aotearoa New Zealand's pandemic experience during the closing months of 2021.

What is said about #donateliver or #liverdonor? Reflexive thematic analysis of Twitter (X) posts from 2012 to 2022.

BACKGROUND: There is sustained interest in understanding the perspectives of liver transplant recipients and living donors, with several qualitative studies shedding light on this emotionally charged subject. However, these studies have relied primarily on traditional semi-structured interviews, which, while valuable, come with inherent limitations. Consequently, there remains a gap in our comprehension of the broader public discourse surrounding living liver donation. This study aims to bridge this gap by delving into public conversations related to living liver donation through a qualitative analysis of Twitter (now X) posts, offering a fresh perspective on this critical issue. METHODS: To compile a comprehensive dataset, we extracted original tweets containing the hashtags "#donateliver" OR "#liverdonor", all posted in English from January 1, 2012, to December 31, 2022. We then selected tweets from individual users whose Twitter (X) accounts featured authentic human names, ensuring the credibility of our data. Employing Braun and Clarke's reflexive thematic analysis approach, the study investigators read and analysed the included tweets, identifying two main themes and six subthemes. The Health Policy Triangle framework was applied to understand the roles of different stakeholders involved in the discourse and suggest areas for policy improvement. RESULTS: A total of 361 unique tweets from individual users were analysed. The major theme that emerged was the persistent shortage of liver donors, underscoring the desperation faced by individuals in need of life-saving liver transplants and the urgency of addressing the organ shortage problem. The second theme delved into the experiences of liver donors post-surgery, shedding light on a variety of aspects related to the transplantation process, including the visibility of surgical scars, and the significance of returning to physical activity and exercise post-surgery. CONCLUSION: The multifaceted experiences of individuals involved in the transplantation process, both recipients and donors, should be further studied in our efforts to improve the critical shortage of liver donors.

Utilizing AI for extracting insights on post WHO's COVID-19 vaccination declaration from X (Twitter) social network.

This study explores the use of artificial intelligence (AI) to analyze information from X (previously Twitter) feeds related to COVID-19, specifically focusing on the time following the World Health Organization's (WHO) vaccination announcement. This aspect of the pandemic has not been studied by other researchers focusing on vaccination news. By utilizing advanced AI algorithms, the research aims to examine a wealth of data, sentiments, and trends to enhance crisis management strategies effectively. Our methods involved collecting a dataset of tweets from December 2020 to July 2021. By using specific keywords strategically, we gathered a substantial 15.5 million tweets, focusing on important hashtags like #vaccine and #coronavirus while filtering out irrelevant replies and retweets. The assessment of three different machine learning models-BiLSTM, FFNN, and CNN - highlights the exceptional performance of BiLSTM, achieving an impressive F1-score of 0.84 on the test set, with Precision and Recall metrics at 0.85 and 0.83, respectively. The study provides a detailed visualization of global sentiments on COVID-19 topics, with a main goal of extracting insights to manage public health crises effectively. Sentiment labels were predicted using various classification models and categorized as positive, negative, and neutral for each country after adjusting for population differences. An important finding from the analysis is the variation in sentiments across regions, for instance, with Eastern European countries showing positive views on post-vaccination economic recovery, while China and the United States express negative opinions on the same topic.

Japanese Perception of Organ Donation and Implications for New Medical Technologies: Quantitative and Qualitative Social Media Analyses.

BACKGROUND: The Rapid Autopsy Program (RAP) is a valuable procedure for studying human biology and diseases such as cancer. However, implementing the RAP in Japan necessitates a thorough understanding of concepts such as good death and the integration of sociocultural aspects. By revising perceptions of organ donation on social media, we bring attention to the challenges associated with implementing new medical research procedures such as the RAP. OBJECTIVE: This study aims to examine YouTube and Twitter/X to identify stakeholders, evaluate the quality of organ donation communication, and analyze sociocultural aspects associated with organ donation. Based on our findings, we propose recommendations for the implementation of new medical research procedures. METHODS: Using the term "" (organ donation), we collected data from YouTube and Twitter/X, categorizing them into 5 dimensions: time, individuality, place, activity, and relationships. We utilized a scale to evaluate the quality of organ donation information and categorized YouTube videos into 3 groups to analyze their differences using statistical methods. Additionally, we conducted a text-based analysis to explore narratives associated with organ donation. RESULTS: Most YouTube videos were uploaded in 2021 (189/638, 29.6%) and 2022 (165/638, 25.9%), while tweets about organ donation peaked between 2019 and 2022. Citizens (184/770, 23.9%), media (170/770, 22.0%), and unknown actors (121/770, 15.7%) were the primary uploaders of videos on organ donation. In a sample of average retweeted and liked tweets, citizens accounted for the majority of identified users (64/91, 70%, and 65/95, 68%, respectively). Regarding Japanese regions, there were numerous information videos about organ donation in Hokkaido (F2.46,147.74=-5.28, P=.005) and Kyushu and Okinawa (F2.46,147.74=-5.28, P=.005). On Twitter/X, Japan and China were the most frequently mentioned countries in relation to organ donation discussions. Information videos often focused on themes such as borrowed life and calls to register as donors, whereas videos categorized as no information and misinformation frequently included accusations of organ trafficking, often propagated by Chinese-American media. Tweets primarily centered around statements of donation intention and discussions about family consent. The majority of video hyperlinks directed users to YouTube and Twitter/X platforms, while Twitter/X hyperlinks predominantly led to news reports from Japanese media outlets. CONCLUSIONS: There is significant potential to implement new medical research procedures such as the RAP in Japan. Recommendations include conceptualizing research data as borrowed data, implementing horizontally diversified management of donation programs, and addressing issues related to science misinformation and popular culture trends.

Current insights on social media as a tool for the dissemination of research and education in surgery: a narrative review.

The purpose of our narrative review is to summarize the utilization of social media (SoMe) platforms for research communication within the field of surgery. We searched the PubMed database for articles in the last decade that discuss the utilization of SoMe in surgery and then categorized the diverse purposes of SoMe. SoMe proved to be a powerful tool for disseminating articles. Employing strategic methods like visual abstracts enhances article citation rates, the impact factor, h-index, and Altmetric score (an emerging alternative metric that comprehensively and instantly quantifies the social impact of scientific papers). SoMe also proved valuable for surgical education, with online videos shared widely for surgical training. However, it is essential to acknowledge the associated risk of inconsistency in quality. Moreover, SoMe facilitates discussion on specific topics through hashtags or closed groups and is instrumental in recruiting surgeons, with over half of general surgery residency programs in the US efficiently leveraging these platforms to attract the attention of potential candidates. Thus, there is a wealth of evidence supporting the effective use of SoMe for surgeons. In the contemporary era where SoMe is widely utilized, surgeons should be well-versed in this evidence.

Twitter Discussions on #digitaldementia: Content and Sentiment Analysis.

BACKGROUND: Digital dementia is a term that describes a possible decline in cognitive abilities, especially memory, attributed to the excessive use of digital technology such as smartphones, computers, and tablets. This concept has gained popularity in public discourse and media lately. With the increasing use of social media platforms such as Twitter (subsequently rebranded as X), discussions about digital dementia have become more widespread, which offer a rich source of information to understand public perceptions, concerns, and sentiments regarding this phenomenon. OBJECTIVE: The aim of this research was to delve into a comprehensive content and sentiment analysis of Twitter discussions regarding digital dementia using the hashtag #digitaldementia. METHODS: Retrospectively, publicly available English-language tweets with hashtag combinations related to the topic of digital dementia were extracted from Twitter. The tweets were collected over a period of 15 years, from January 1, 2008, to December 31, 2022. Content analysis was used to identify major themes within the tweets, and sentiment analysis was conducted to understand the positive and negative emotions associated with these themes in order to gain a better understanding of the issues surrounding digital dementia. A one-way ANOVA was performed to gather detailed statistical insights regarding the selected tweets from influencers within each theme. RESULTS: This study was conducted on 26,290 tweets over 15 years by 5123 Twitter users, mostly female users in the United States. The influencers had followers ranging from 20,000 to 1,195,000 and an average of 214,878 subscribers. The study identified four themes regarding digital dementia after analyzing tweet content: (1) cognitive decline, (2) digital dependency, (3) technology overload, and (4) coping strategies. Categorized according to Glaser and Strauss's classifications, most tweets (14,492/26,290, 55.12%) fell under the categories of wretched (purely negative) or bad (mostly negative). However, only a small proportion of tweets (3122/26,290, 11.86%) were classified as great (purely positive) or swell sentiment (mostly positive). The ANOVA results showed significant differences in mean sentiment scores among the themes (F3,3581=29.03; P<.001). The mean sentiment score was -0.1072 (SD 0.4276). CONCLUSIONS: Various negative tweets have raised concerns about the link between excessive use of digital devices and cognitive decline, often known as digital dementia. Of particular concern is the rapid increase in digital device use. However, some positive tweets have suggested coping strategies. Engaging in digital detox activities, such as increasing physical exercise and participating in yoga and meditation, could potentially help prevent cognitive decline.

Emergency communication networks on Twitter during Hurricane Irma: information flow, influential actors, and top messages.

This study combined network analysis with message-level content analysis to investigate patterns of information flow and to examine messages widely distributed on social media during Hurricane Irma of 2017. The results show that while organisational users and media professionals dominated the top 100 information sources, individual citizens played a critical role in information dissemination. Public agencies should increase their retweeting activities and share the information posted by other trustworthy sources; doing so will contribute to the timely exchange of vital information during a disaster. This study also identified the active involvement of nonprofit organisations as information brokers during the post-event stage, indicating the potential for emergency management organisations to integrate their communication efforts into those of nonprofit entities. These findings will inform emergency management practices regarding implementation of communication plans and policies, facilitate the embracement of new partner organisations, and help with establishing and sustaining effective communication ties with a wide range of stakeholders.

Misinformation surrounding sodium reduction for blood pressure: content analysis of Japanese posts on X.

This content analysis aimed to assess misinformation themes regarding sodium reduction and blood pressure on X with the goal of providing strategies to address and debunk such misinformation. A total of 531 posts were manually coded into sodium-related misinformation themes, with inclusion criteria for posts asserting no association between sodium reduction and hypertension or claiming consuming sodium is beneficial for health. Numbers and post frequencies per misinformation theme were calculated. Post characteristics, including information sources, advertisements and narratives, were coded, and a correlation analysis was conducted to assess their association with each misinformation theme. Fourteen sodium-related misinformation themes were identified and consistently disseminated on X. The predominant theme, 'Natural Salt', accounted for 37.7% (n = 200), reaching 1.6 million followers, followed by 'Reducing salt could be bad for my health' theme, comprising 28.6% (n = 152) and reaching 1.5 million followers. There was a statistical correlation between the natural salt misinformation theme and advertisements. Many of the most frequent misinformation themes identified in this study have not been systematically debunked by organizations such as the World Health Organization and the American Heart Association. This study underscores the importance of continuous monitoring and analysis of sodium-related misinformation on social media platforms and their underlying commercial interests. Such monitoring has the potential to identify prevalent misinformation themes that may pose harm to the public and to inform public health organizations, enabling them to proactively address potential issues through debunking.

Nutrients and Foods Recommended for Blood Pressure Control on Twitter in Japan: Content Analysis.

BACKGROUND: Management and prevention of hypertension are important public health issues. Healthy dietary habits are one of the modifiable factors. As Twitter (subsequently rebranded X) is a digital platform that can influence public eating behavior, there is a knowledge gap regarding the information about foods and nutrients recommended for blood pressure control and who disseminates them on Twitter. OBJECTIVE: This study aimed to investigate the nature of the information people are exposed to on Twitter regarding nutrients and foods for blood pressure control. METHODS: A total of 147,898 Japanese tweets were extracted from January 1, 2022, to December 31, 2022. The final sample of 2347 tweets with at least 1 retweet was manually coded into categories of food groups, nutrients, user characteristics, and themes. The number and percentage of tweets, retweets, and themes in each category were calculated. RESULTS: Of the 2347 tweets, 80% (n=1877) of tweets mentioned foods, which were categorized into 17 different food groups. Seasonings and spices, including salt, were most frequently mentioned (1356/1877, 72.2%). This was followed by vegetable and fruit groups. The 15 kinds of nutrients were mentioned in 1566 tweets, with sodium being the largest proportion at 83.1% (n=1301), followed by potassium at 8.4% (n=132). There was misinformation regarding salt intake for hypertension, accounting for 40.8% (n=531) of tweets referring to salt, including recommendations for salt intake to lower blood pressure. In total, 75% (n=21) of tweets from "doctors" mentioned salt reduction is effective for hypertension control, while 31.1% (n=74) of tweets from "health, losing weight, and beauty-related users," 25.9% (n=429) of tweets from "general public," and 23.5% (n=4) tweets from "dietitian or registered dietitian" denied salt reduction for hypertension. The antisalt reduction tweets accounted for 31.5% (n=106) of the most disseminated tweets related to nutrients and foods for blood pressure control. CONCLUSIONS: The large number of tweets in this study indicates a high interest in nutrients and foods for blood pressure control. Misinformation asserting antisalt reduction was posted primarily by the general public and self-proclaimed health experts. The number of tweets from nutritionists, registered dietitians, and doctors who were expected to correct misinformation and promote salt reduction was relatively low, and their messages were not always positive toward salt reduction. There is a need for communication strategies to combat misinformation, promote correct information on salt reduction, and train health care professionals to effectively communicate evidence-based information on this topic.

Tweeting about fatphobia and body shaming: A retrospective infodemiological study.

BACKGROUND: We aimed to analyze reactions to tweets that employed weight-based discrimination terms and to compare them to others posted by the same users on X (formerly Twitter). METHODS: We collected tweets featuring weight-based discrimination terms (the study group) and created a control group by randomly selecting up to five tweets from each account that did not mention any such terms. Descriptive statistics, sentiment analysis, and logistic regression modeling were used to compare the numbers of likes and retweets of the study and control groups, and to understand the emotions associated with these tweets. RESULTS: Our analysis included 22,075 study group tweets and 50,341 control group tweets. Sentiment analysis was conducted on 41,403 (57.2%) tweets, with 65.7% of the study group tweets being found to contain negative sentiments. The study group had a higher median of likes (1 [0-4]) and retweets (0 [0-0]) than the control group (1 [0-2] and 0 [0-0], respectively, with the study group obtaining higher mean ranks in both comparisons, P < 0.001). Multivariable logistic regression analysis revealed that tweets using weight-based discrimination terms gained more likes (OR = 1.22; 95% CI: 1.16-1.28) and retweets (OR = 1.61; 95% CI: 1.49-1.74), independent of, for example, verification status, follower count, year and season of the tweet, and emotional expression of the tweet. CONCLUSIONS: Tweets concerning fatphobia, body shaming, and similar terms gain more reactions than others posted by the same accounts.

Investigating Health and Well-Being Challenges Faced by an Aging Workforce in the Construction and Nursing Industries: Computational Linguistic Analysis of Twitter Data.

BACKGROUND: Construction and nursing are critical industries. Although both careers involve physically and mentally demanding work, the risks to workers during the COVID-19 pandemic are not well understood. Nurses (both younger and older) are more likely to experience the ill effects of burnout and stress than construction workers, likely due to accelerated work demands and increased pressure on nurses during the COVID-19 pandemic. In this study, we analyzed a large social media data set using advanced natural language processing techniques to explore indicators of the mental status of workers across both industries before and during the COVID-19 pandemic. OBJECTIVE: This social media analysis aims to fill a knowledge gap by comparing the tweets of younger and older construction workers and nurses to obtain insights into any potential risks to their mental health due to work health and safety issues. METHODS: We analyzed 1,505,638 tweets published on Twitter (subsequently rebranded as X) by younger and older (aged <45 vs >45 years) construction workers and nurses. The study period spanned 54 months, from January 2018 to June 2022, which equates to approximately 27 months before and 27 months after the World Health Organization declared COVID-19 a global pandemic on March 11, 2020. The tweets were analyzed using big data analytics and computational linguistic analyses. RESULTS: Text analyses revealed that nurses made greater use of hashtags and keywords (both monograms and bigrams) associated with burnout, health issues, and mental health compared to construction workers. The COVID-19 pandemic had a pronounced effect on nurses' tweets, and this was especially noticeable in younger nurses. Tweets about health and well-being contained more first-person singular pronouns and affect words, and health-related tweets contained more affect words. Sentiment analyses revealed that, overall, nurses had a higher proportion of positive sentiment in their tweets than construction workers. However, this changed markedly during the COVID-19 pandemic. Since early 2020, sentiment switched, and negative sentiment dominated the tweets of nurses. No such crossover was observed in the tweets of construction workers. CONCLUSIONS: The social media analysis revealed that younger nurses had language use patterns consistent with someone experiencing the ill effects of burnout and stress. Older construction workers had more negative sentiments than younger workers, who were more focused on communicating about social and recreational activities rather than work matters. More broadly, these findings demonstrate the utility of large data sets enabled by social media to understand the well-being of target populations, especially during times of rapid societal change.