A Thematic Analysis of Weibo Topics (Chinese Twitter Hashtags) Regarding Older Adults During the COVID-19 Outbreak

Exploring Iranian sentiments on the Paris Agreement: Insights from Twitter

Iran remains one of the few nations not fully committed to the Paris Agreement and public opinion regarding implementation of policies serves a significant role. This study examines the general sentiment of Iranian Twitter users towards the Paris Agreement. A total of 25,386 tweets were collected and analyzed, revealing that discussions around the Paris Agreement predominantly centred on terms such as 'electricity', 'shameful', 'government', and 'America'. The majority of these tweets coincided with the power outages in January, June, and July 2021, as well as the period following Trump's withdrawal from the Paris Agreement in June 2017. To gain deeper insights into the level of support for the Paris Agreement in Iran, a thematic analysis was conducted on a random sample of 500 tweets, selected based on the theoretical saturation of themes and sub-themes. The analysis revealed that 8 % of users expressed a positive orientation, 60 % a negative orientation, and 32 % a neutral orientation towards the Paris Agreement. The thematic analysis suggests that the negative sentiment is primarily due to frequent power outages, perceived inefficiency and lack of trust in government decisions, lack of transparency, and the perceived colonial nature of the agreement for developing countries. The findings underscore the importance of garnering public support in developing countries for international environmental agreements.

Unraveling the Use of Disinformation Hashtags by Social Bots During the COVID-19 Pandemic: Social Networks Analysis

BACKGROUND

During the COVID-19 pandemic, social media platforms have been a venue for the exchange of messages, including those related to fake news. There are also accounts programmed to disseminate and amplify specific messages, which can affect individual decision-making and present new challenges for public health.

OBJECTIVE

This study aimed to analyze how social bots use hashtags compared to human users on topics related to misinformation during the outbreak of the COVID-19 pandemic.

METHODS

We selected posts on specific topics related to infodemics such as vaccines, hydroxychloroquine, military, conspiracy, laboratory, Bill Gates, 5G, and UV. We built a network based on the co-occurrence of hashtags and classified the posts based on their source. Using network analysis and community detection algorithms, we identified hashtags that tend to appear together in messages. For each topic, we extracted the most relevant subtopic communities, which are groups of interconnected hashtags.

RESULTS

The distribution of bots and nonbots in each of these communities was uneven, with some sets of hashtags being more common among accounts classified as bots or nonbots. Hashtags related to the Trump and QAnon social movements were common among bots, and specific hashtags with anti-Asian sentiments were also identified. In the subcommunities most populated by bots in the case of vaccines, the group of hashtags including #billgates, #pandemic, and #china was among the most common.

CONCLUSIONS

The use of certain hashtags varies depending on the source, and some hashtags are used for different purposes. Understanding these patterns may help address the spread of health misinformation on social media networks.

Social support and audience engagement of lupus-related posts on social networking sites in China

Background

Lupus, known as a chronic multisystem autoimmune disease, has become more common in China currently. Above all, most Chinese Lupus patients haven't ample knowledge and adequate understanding of this complicated chronic disease. In recent years, social networking sites have created an interactive environment in which patients can obtain health information and also can exchange personal experiences with others having similar health concerns.

Objective

The overall aim of this study is to develop a better understanding of the social support requested and received during the routine social media use of lupus activists and their referents. In other words. This paper seeks to explore whether the lupus-related posts disseminated on the Sina microblog platform can serve and satisfy the needs of this group.

Methods

Content analysis and descriptive analysis were conducted to ascertain the core topics of lupus-related posts on the Sina microblog. Chi-square tests were performed to determine the differences in types of social support between provision and request groups, as well as engaged and non-engaged groups. Finally, negative binomial regression was undertaken to investigate which types of social support generated more audience engagement.

Results

By analyzing 9822 lupus-related posts derived from the Sina microblog, disease description was the most prominent theme. Evidence is presented which shows that information support was requested and supplied more frequently than emotional and instrumental support. Specifically, information support was provided more than requested, while the instrumental and emotional support provisions were less numerous than the requests. Analysis revealed that posts containing information support provisions attracted more engagement than those with the other five types of social support.

Conclusions

Social networking sites play a critical role on disseminating lupus-related information and provide an interactive space in which users can freely communicate their health conditions and seek peer support. However, health practitioners not only have to present more communication strategies to provide emotional and instrumental support through social media, but also have to boost audience engagement.

Criticism, Compassion, and Conspiracy Theories: A Thematic Analysis of What Twitter Users Are Saying About COVID-19 in Correctional Settings

We examined Twitter data using thematic analysis to understand public perceptions of the impact of COVID-19 on incarcerated people and reactions to including incarcerated populations in the early phases of the vaccine rollout. Our findings from n = 513 Tweets yielded six themes: Twitter as usual, Advocacy, Deserve to suffer, Vaccine priority debate, Inadequate response, and Misinformation. Stigma-laden statements cut across themes, highlighting the role pathologizing beliefs play in forming opinions about incarcerated people in public health crises. Trust of government response and buy-in to public health communication are positively associated with adherence to guidelines. Although public health decisions are derived from logic and research, our findings indicate that public perception may be driven by personal morals and stigma associated with justice-involved individuals. We recommend that attention be turned toward effective policy messaging, and use of social media, to increase trust and decrease stigma that tends to dominate societal perception.

Examining Public Awareness of Ageist Terms on Twitter: Content Analysis

Background

The World Health Organization, the Centers for Disease Control and Prevention, and the Gerontological Society of America have made efforts to raise awareness on ageist language and propose appropriate terms to denote the older adult population. The COVID-19 pandemic and older adults' vulnerability to the disease have perpetuated hostile ageist discourse on social media. This is an opportune time to understand the prevalence and use of ageist language and discuss the ways forward.

Objective

This study aimed to understand the prevalence and situated use of ageist terms on Twitter.

Methods

We collected 60.32 million tweets between March and July 2020 containing terms related to COVID-19. We then conducted a mixed methods study comprising a content analysis and a descriptive quantitative analysis.

Results

A total of 58,930 tweets contained the ageist terms "old people" or "elderly." The more appropriate term "older adult" was found in 11,328 tweets. Twitter users used ageist terms (eg, "old people" and "elderly") to criticize ageist messages (17/60, 28%), showing a lack of understanding of appropriate terms to describe older adults. Highly hostile ageist content against older adults came from tweets that contained the derogatory terms "old people" (22/30, 73%) or "elderly" (13/30, 43%).

Conclusions

The public discourse observed on Twitter shows a continued lack of understanding of appropriate terms to use when referring to older adults. Effort is needed to eliminate the perpetuation of ageist messages that challenge healthy aging. Our study highlights the need to inform the public about appropriate language use and ageism.

Greenspace exposure is conducive to the resilience of public sentiment during the COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic significantly impacts people's sentiment and mental health, threatening their health and lives. We gathered 4.17 million geotagged social media posts from Weibo and scrutinized the nuances of the collective sentiments of netizens in four megacities in China during the first pandemic wave (from 1 December 2019 to 30 April 2020). Our findings suggest that the COVID-19 outbreak significantly reduced the Sentiment Index (SI) in China's cities, and the collective sentiments expressed in Wuhan were even more negative than those in the other three megacities. We explored the uncharted impacts of exposure to three geographical environment factors (GEFs) on SIs. Public exposure to greenspaces increased, while exposure to indoor built spaces decreased during the lockdown period. The exposure to sidewalks increased in rural areas but decreased in the main urban areas. The contributions of various GEFs to the SIs were the lowest during the lockdown period, and SIs were strongly affected by the pandemic. However, greenspace had the most potent effect on SIs, improving public sentiment resilience and mitigating mental health risks.

Videos about older adults on TikTok

Besides being one of the fastest growing platforms since entering the social media fray in 2016, TikTok is notably monopolized by teenagers, which makes it a veritable source of information not to be overlooked by gerontologists. Currently, most studies regarding age stereotypes on social media have examined content on Twitter and Facebook. Our study explores how older adults are portrayed on TikTok and the factors associated with these portrayals. We analyzed 673 videos with the hashtags #Boomer and/or #OkBoomer that received over 5.4 billion views and categorized them into nine topics. Five of these topics (e.g., 'Warmth/Coldness') were extracted from previous studies on age stereotypes. The remaining four topics were unique to our dataset (e.g., 'Wealth Gap'). The outcome variable was 'Negative Age Stereotypes' which was rated on a binary scale. One in two videos about older adults featured negative content. As hypothesized, videos containing negative age stereotypes were more likely to be about the 'Values and Beliefs of Older Adults' (7 times), 'Negative Encounters with Older Adults' (8 times) or 'Older Adults Antagonizing the Young' (13 times). Conversely, videos which portrayed older adults as 'Warm' were 43% less likely to contain negative stereotypes. As the phenomenon of an aging population fast unfolds, it is imperative that society relinquishes its tendency to stereotype individuals on the grounds of age. By examining the possible mechanisms driving negative stereotypes of older adults on TikTok, our study provides the basis upon which such stereotypes can be counteracted. In doing so, it paves the way both to improve the well-being of older persons and to foster intergenerational solidarity.

Challenges and countermeasures of China's research on "sports promoting adolescent socialization"-data mining based on Weibo and CNKI

Objective

Understand the public demand for Adolescent socialization, and compare the hot spots in the researches of "sports promoting Adolescent socialization," so as to clarify the high-quality development direction of sports promoting Adolescent socialization in the new era.

Methods

Collected the Weibo texts about "Adolescent socialization" from April 13, 2017 to June 1, 2022 through python, and used LDA to understand the relevant hot spots. Used City space to collect CNKI studies related to "sports promote Adolescent socialization," and used keyword co-occurrence network to understand hot spots.

Results

A total of 77,900 original Weibo texts were captured. The theme model identified five potential themes: "School and Family Education," "Social Participation," "Community Education," "Ideological and Political Education" and "Media." The semantic network showed that the public concerns of each theme include "Adolescent socialization education content," "relevant policies and regulations," "Adolescent socialization environment," "traditional culture" and "publicity ways and examples"0.52 studies were finally retrieved. The keyword co-occurrence network showed that keywords such as "Adolescent," "Socialization," "Sports Games," "School Sports" and "Family Sports" appeared more frequently and had higher intermediary centrality. Researches focused on Socialization, Internet Addiction, Coupling, School Sports, Sports Socialization Media.

Conclusion

The public's attention to "Adolescent socialization" has three characteristics: subject linkage, object susceptibility, and media diversity. The researches on "Sports Promoting the socialization of Adolescents" has some problems, such as the imbalance of subject supply and demand, the inconsistent way of object supply and demand, and the different content of media supply and demand. The reason is that there is an information island between people and scholars. Existing research results can not meet the demands of the public.

Being Called "Elderly" Impacts Adult Development: A Critical Analysis of Enduring Ageism During COVID in NZ Online News Media

This article examines how “the elderly” is constructed in New Zealand online news media. By employing a critical framing analysis to challenge ageist practices, conceptually, the study adds to our knowledge of research methodologies in the field of adult development. Online news media articles were collected and analyzed to understand constructions of older adults as “elderly” over an 18-month period before, during, and since the COVID pandemic. Results demonstrated that the term “elderly” was framed powerlessly, in predominantly negative (74%) stereotypical messages about older adults. Positive stereotypes (26% of data) used human impact framing. Associations of “elderly” with being vulnerable, declining, and an individual or societal burden have serious implications, notably for the media in their role of both constructing and reflecting societal attitudes and actions towards older adults. Suggestions are offered to encourage reframing societal attitudes and promoting healthy adult development through age-equality messages that do away with the term “elderly.”

Social trust and stress symptoms among older adults during the COVID-19 pandemic: evidence from Asia

Objectives

To investigate whether social trust is associated with more stress symptoms among middle-aged and older adults in six East and Southeast Asia regions during the COVID-19 pandemic.

Methods

This multi-region study used cross-sectional survey data collected in May 2020. Participants were a probability-based internet sample of adults aged 55 or older.

Results

Government trust was negatively associated with stress in Singapore and South Korea. Higher levels of health care trust were significantly associated with less stress in Singapore and Taiwan. Trust in neighbors was associated with a higher likelihood of stress in Hong Kong and a lower likelihood in Singapore. Social trust was not associated with stress in Japan or Thailand.

Discussion

Findings suggest the level of social trust in relation to stress substantially varied by region. Interventions to strengthen trust during COVID-19 and other major health crises need to be tailored to fit regions’ unique circumstances.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-02847-5.

We Were All Once Young: Reducing Hostile Ageism From Younger Adults' Perspective

The worldwide spreading pandemic, COVID-19, has caused hostile ageism toward older adults. We adopted a new intervention to reduce such hostile ageism. “Imagine that they were Young” referred to the imagination of what an older adult might look like, think, and behave when they were once young, which was a reversed but refined intervention of the widely-used method of “Imagine that you were old.” In the present study, intergenerational tension was primed, and then 205 younger adults in China aged 18–37 were randomly assigned to 3 different conditions (“Imagine that they were Young,” “Imagine that you were old,” and control condition), asking them to imagine (and then write down) once older adults were young, or a future aging self, or read an unrelated essay respectively as experimental manipulations. Then they should distribute medical funds worthy of Chinese 1 million to two patients with COVID-19 of 25 and 85 years old indicating their attitudes toward older adults (or hostile ageism). Finally, we measured their general attitudes and stereotypes toward older adults. Results verified the effectiveness of both interventions, such that younger adults who took either intervention distributed more medical funds and showed more positive aging attitudes toward older adults than those in the control group. Moreover, “Imagine that they were Young” was tested to be even more effective than “Imagine that you were old.” A series of relative mediation models revealed that the stereotype of warmth mediated the effect for both interventions on decreased hostile ageism behaviors, compared with the control condition. While “Imagine that they were Young” could additionally reduce hostile ageism through a higher level of “including the older adults in their self-group (the young).” This new intervention might be a good alternative to eliminate hostile ageism.

Temporal Variations and Spatial Disparities in Public Sentiment Toward COVID-19 and Preventive Practices in the United States: Infodemiology Study of Tweets

Background

During the COVID-19 pandemic, US public health authorities and county, state, and federal governments recommended or ordered certain preventative practices, such as wearing masks, to reduce the spread of the disease. However, individuals had divergent reactions to these preventive practices.

Objective

The purpose of this study was to understand the variations in public sentiment toward COVID-19 and the recommended or ordered preventive practices from the temporal and spatial perspectives, as well as how the variations in public sentiment are related to geographical and socioeconomic factors.

Methods

The authors leveraged machine learning methods to investigate public sentiment polarity in COVID-19–related tweets from January 21, 2020 to June 12, 2020. The study measured the temporal variations and spatial disparities in public sentiment toward both general COVID-19 topics and preventive practices in the United States.

Results

In the temporal analysis, we found a 4-stage pattern from high negative sentiment in the initial stage to decreasing and low negative sentiment in the second and third stages, to the rebound and increase in negative sentiment in the last stage. We also identified that public sentiment to preventive practices was significantly different in urban and rural areas, while poverty rate and unemployment rate were positively associated with negative sentiment to COVID-19 issues.

Conclusions

The differences between public sentiment toward COVID-19 and the preventive practices imply that actions need to be taken to manage the initial and rebound stages in future pandemics. The urban and rural differences should be considered in terms of the communication strategies and decision making during a pandemic. This research also presents a framework to investigate time-sensitive public sentiment at the county and state levels, which could guide local and state governments and regional communities in making decisions and developing policies in crises.

What social media told us in the time of COVID-19: a scoping review

With the onset of the COVID-19 pandemic, social media has rapidly become a crucial communication tool for information generation, dissemination, and consumption. In this scoping review, we selected and examined peer-reviewed empirical studies relating to COVID-19 and social media during the first outbreak from November, 2019, to November, 2020. From an analysis of 81 studies, we identified five overarching public health themes concerning the role of online social media platforms and COVID-19. These themes focused on: surveying public attitudes, identifying infodemics, assessing mental health, detecting or predicting COVID-19 cases, analysing government responses to the pandemic, and evaluating quality of health information in prevention education videos. Furthermore, our Review emphasises the paucity of studies on the application of machine learning on data from COVID-19-related social media and a scarcity of studies documenting real-time surveillance that was developed with data from social media on COVID-19. For COVID-19, social media can have a crucial role in disseminating health information and tackling infodemics and misinformation.

COVID-19 in LMICs: The Need to Place Stigma Front and Centre to Its Response

COVID-19 has caused unprecedented health, economic and societal impacts across the world, including many low- and middle-income countries (LMICs). The pandemic and its fallout have laid bare deep-seated social and economic inequalities with marginalised groups being at greater risk of infection and being disproportionately affected by containment measures and their socioeconomic consequences. Stigma is a central element to such inequalities but remains largely overlooked in the debate on the response to COVID-19, including in LMICs. Yet we know from experiences with other infectious diseases such as HIV/AIDS and Ebola that disease-related stigma is detrimental to halting and controlling pandemics and achieving equitable development. Emerging evidence suggests that stigma associated with COVID-19 is already taking hold. This paper assesses potential driving factors of COVID-19-related stigma, and how this intersects with existing stigma fault lines and explores mechanisms through which COVID-19-related stigma may be counteracted, with a focus on LMICs.