Individuals suffering from social anxiety disorder (SAD) are increasingly turning to online support communities for self-disclosure and social support. Despite the extensive body of research on online mental health discourses, the cultural nuances within SAD-related discussions remain underexplored. In this study, we examine the cultural differences in online expression of social anxiety by analyzing individuals\' self-disclosure and support-seeking behaviors in social media posts. Using two-week data (n = 1,681) from two SAD support communities on the Reddit and Douban groups, we used both qualitative thematic analysis and quantitative semantic analysis to discern prevalent themes and linguistic attributes characterizing these online expressions. Our findings not only uncover common themes such as sharing personal experiences and seeking mutual validations in both communities but also identify their divergences, as Western users primarily sought advice and information in posts, whereas Chinese users were more inclined toward networking. Cultural variations in language use were evident, particularly in individuals\' affect and their expression of personal and social concerns. Western users were more likely to convey negative emotions and delve into personal matters related to SAD, whereas Chinese users tended to grapple more with workplace anxieties. This study contributes to the cultural understanding of online mental health discourses and offers insights for crafting culturally sensitive interventions and supports for people with SAD.

In China, condomless sex among men who have sex with men (MSM) is the primary route of HIV infection in young people. Chengdu is a hotspot for reported HIV cases among young people nationwide. Extensive use of geosocial networking (GSN) smartphone apps has dramatically changed the pattern of sexual behavior among young MSM (YMSM). However, data on HIV incidence and the risk behavior of YMSM using the GSN app are still obscure.
This study aims to analyze and understand the HIV incidence and its risk factors among YMSM using GSN apps in Chengdu, China.
An open cohort study was conducted among YMSM aged 18-24 years through a gay GSN smartphone app in Chengdu, China, from July 2018 to December 2020. Every participant completed a web-based questionnaire on sociodemographic characteristics, sexual behaviors, and other related statuses; made a reservation for a web-based HIV testing; and then voluntarily got tested at the designated testing site. At least one additional HIV test was taken via the app during the study period, and participants were evaluated at the end of the study or at the time of HIV seroconversion. By dividing the sum of the observed HIV seroconversions by the observed person-years, HIV incidence was calculated and compared between the student and nonstudent MSM. Univariate and multivariate (Cox proportional hazards regression) analyses were used to discuss the risk factors for new HIV infections.
In the study cohort, 24 seroconversions occurred among 625 YMSM who took at least two HIV tests through the app during the study period, contributing to 505 observed person-years. The HIV incidence rate per 100 person-years was 4.75 (95% CI 2.89-6.61) among all MSM, 3.60 (95% CI 1.27-5.93) among student MSM, and 5.88 (95% CI 2.97-8.79) among nonstudent MSM. In addition, the HIV incidence per 100 person-years was 11.11 (95% CI 4.49-17.73) among those who had resided in the area for 6 months or less and 7.14 (95% CI 1.52-12.77) among those with senior high school or less education. Two or more sexual partners (adjusted hazards ratio [HR] 3.63, 95% CI 1.08-12.23) in the preceding 6 months was a risk factor for new HIV infections. Consistent condom use for anal sex (adjusted HR 0.38, 95% CI 0.16-0.88) and insertive anal sex only (adjusted HR 0.10, 95% CI 0.01-0.75) in the preceding 6 months were protective factors for new HIV infections.
The rate of new HIV infections among YMSM who actively used GSN smartphone apps was high, especially among migrant nonstudent MSM. Targeted interventions on GSN smartphone apps should be implemented to provide demand-adapted prevention and services to reduce the threat of HIV.

Drawing upon the concept of longitudinal multiplexity and the Institutional Collection Action (ICA) framework, this article conducts a longitudinal observation of online emergency collaborative networks (ECNs) built and sustained among organizational actors within Shenzhen and Hong Kong in response to Typhoon Mangkhut. In addition to investigating the multiplex relationships among three types of online ECNs (i.e., preparedness networks, response networks, recovery networks), this article takes a comparative approach to examining how the structural constraints imposed by distinct emergency management systems (EMSs) influence the network formation and evolution as the disaster evolves over time. Findings obtained from a series of inferential network analyses reveal that preexisting online collaborative ties formed at the disaster preparedness stage are important for increasing organizations\' tendency to build and sustain online collaborations during disaster response and recovery. Moreover, the decentralized EMS in Hong Kong exhibits more effectiveness in facilitating online network changes during both transitional periods. These findings demonstrate a pressing need for emergency researchers and frontline communication managers to understand the dynamic relationships among online ECNs across different disaster phases and further explore potential opportunities to facilitate online emergency collaboration on a broader scale.

Accessing medical resources has been a challenging issue in China, particularly for people who do not live in big cities. Online \"Ask the doctor\" (AtD) services are gaining popularity rapidly. On AtDs, patients or their caregivers can ask questions to medical professionals and receive medical advice without going through the hassles of visiting local hospitals or doctors\' offices. However, the communication patterns and remaining challenges of this tool are understudied.
The purpose of this study was to (1) explore the dialogue patterns between the patients and the doctors on an AtD service in China, (2) identify issues and remaining challenges in this new form of communication.
We conducted an exploratory study to analyze the dialogues between patients and doctors as well as patients\' reviews. To analyze the dialogue data, we took inspiration from the discourse analysis and focus on the various components of the dialogues. We also used thematic analysis to discover the underlying themes embedded in each dialogue, and identify themes from patient complaints.
We identified four stages in the dialogues between the patients and doctors, including the initiating stage, continuing stage, ending stage, and following up stage. We also summarized the common patterns in the first three stages and reasons for sending follow-up messages. Moreover, we identified 6 unique challenges of the AtD service, including (1) inefficient communication in the initial stage, (2) unfinished conversation in the ending stage, (3) communication is perceived as real-time by the patients, not by the doctors, (4) drawbacks of voice messages, (5) verge of the illegal behaviors, and (6) consultation is not worth the payment.
The AtD service provides the follow-up communication pattern which is considered as a good supplement of Chinese traditional health care. However, several barriers, such as ethical problems, mismatched perceptions and expectations, cost-effectiveness issue still need further investigation.

During the COVID-19 pandemic, adolescents\' use of social networking sites/apps has surged, and their mental health and quality of life have also been significantly affected by the pandemic and its associated social-protection measures. The present study first examined the prevalence of social networking sites/apps use and social networking addiction, the mental health status, and the health-related quality of life among Hong Kong adolescent students. We further investigated the associations of the youths\' daily use of social networking sites/apps and their social networking addiction with their mental health and quality of life during the pandemic.
A total of 1,147 students (age = 15.20 ± 0.53 years) recruited from 12 randomly selected local secondary schools in Hong Kong participated in a questionnaire survey in classroom settings between January and June, 2020, right after the COVID-19 outbreak. The questionnaire includes demographic characteristics and scales that measure social networking sites/apps use and social networking addiction, mental health, and quality of life.
Approximately 46.4% of the participants reported using social networking sites/apps often or very often, and 7.8% met the criteria for social networking addiction using Bergen\'s Social Media Addiction Scale. The prevalence of mild to extremely severe depression, anxiety, and stress among the adolescents stood at 39.6, 37.5, 48.8%, respectively, and the participants\' physical, social, and school functioning were lower than the norms of healthy adolescents before the pandemic. Participants who used social networking sites/apps but for <3 h per day (excluding students who never used social networking sites/apps) showed significantly fewer problems of depression, anxiety, and stress than did those who spent more than 3 h per day on social networking sites/apps. Social networking addiction was found to be consistently associated with poor mental health and health-related quality of life.
This study provides important evidence supporting the potential protective effect of guiding adolescents to use social networking sites/apps appropriately in order to mitigate their negative emotions during contexts such as that of the pandemic; it further points to the need to provide extra support to promote the well-being of young people, especially those in disadvantaged situations (e.g., non-intact family) during and after the pandemic.

To investigate the longitudinal prediction of intensity and emotional connection (EC) related to online social networking use at baseline on the risk of incident depression at nine-month follow-up among adolescents.
A total of 3196 secondary school students, who were online social networking users and free of depression at baseline, were included in this study. Multilevel logistic regression models were applied to investigate the longitudinal prediction of two dimensions of online social networking use intensity (social function use intensity (SFUI), entertainment function use intensity (EFUI)) and EC scores at baseline on incident depression at follow-up.
The incidence of depression was 23.37 per 100-person-years during a nine-month follow-up period. Baseline SFUI and EFUI scores were significantly associated with higher level of incident depression (adjusted OR = 1.017, 95% CI: 1.004-1.029 for SFUI, p = 0.010; adjusted OR = 1.046, 95% CI: 1.012-1.080 for EFUI, p = 0.007), after adjustment of significant background factors and baseline depressive symptom score. The associations of EC at baseline and its interaction with SFUI and EFUI on incident depression were statistically non-significant.
Online social networking use seems be a risk factor of depression among adolescents, regardless of its specific functions. Early intervention is recommended to reduce the level of online social networking use intensity as a means of preventing depression among adolescents.

Network interaction has evolved into a grouping paradigm as civilization has progressed and artificial intelligence technology has advanced. This network group model has quickly extended communication space, improved communication content, and tailored to the demands of netizens. The fast growth of the network community on campus can assist students in meeting a variety of communication needs and serve as a vital platform for their studies and daily lives. It is investigated how to extract opinion material from comment text. A strategy for extracting opinion attitude words and network opinion characteristic words from a single comment text is offered at a finer level. The development of a semiautonomous domain emotion dictionary generating technique improves the accuracy of opinion and attitude word extraction. This paper proposes a window-constrained Latent Dirichlet Allocation (LDA) topic model that improves the accuracy of extracting network opinion feature words and ensures that network opinion feature words and opinion attitude words are synchronized by using the location information of opinion attitude words. The two-stage opinion leader mining approach and the linear threshold model based on user roles are the subjects of model simulation tests in this study. It is demonstrated that the two-stage opinion leader mining method suggested in this study can greatly reduce the running time while properly finding opinion leaders with stronger leadership by comparing the results with existing models. It also shows that the linear threshold model based on user roles proposed in this paper can effectively limit the total number of active users who are activated multiple times during the information diffusion process by distinguishing the effects of different user roles on the information diffusion process.

The potential mechanisms underlying the association between online social networking use intensity and depressive symptoms are unclear and underresearched.
We aimed to investigate the potential roles of interpersonal psychosocial factors on the association between online social networking use intensity and depressive symptoms among early adolescents.
A total of 4237 adolescents from a 9-month longitudinal study were included. Score changes (indicated as △) for the social function use intensity (SFUI) and entertainment function use intensity (EFUI) subscales of the Online Social Networking Activity Intensity Scale and for friendship quality, perceived family support, perceived friend support, parent-adolescent conflict, social nonconfidence, and depressive symptoms were analyzed. The potential mediation effects of unfavorable psychosocial factors and suppression effects of favorable psychosocial factors on the association of △SFUI with △CES-D and the association of △EFUI with △CES-D were tested using hierarchical regression models.
The association between △SFUI and △CES-D was partially mediated by △mother-adolescent conflict (mediation effect size 5.11%, P=.02) and △social nonconfidence (mediation effect size 20.97%, P<.001) but partially suppressed by △friendship quality, △perceived family support, and △perceived friend support, with suppression effects of -0.011 (P=.003), -0.009 (P=.003), and -0.022 (P<.001), respectively. The association between △EFUI and △CES-D was partially mediated by △social nonconfidence (mediation effect size 30.65%, P<.001) but partially suppressed by △perceived family support and △perceived friend support, with suppression effects of -0.036 (P<.001) and -0.039 (P<.001), respectively.
The association between online social networking use intensity and depressive symptoms was partially mediated through the indirect increase in social nonconfidence and mother-adolescent conflict; however, better perceived social support and friendship quality would partially compensate for the harmful impact of online social networking use intensity on depressive symptoms among early adolescents.

The outbreak of a novel coronavirus pneumonia (COVID-19), wherein more than 200 million people have been infected and millions have died, poses a great threat to achieving the United Nations 2030 sustainable development goal (SDGs). Based on the Baidu index of \'novel coronavirus\', this paper analyses the spatial and temporal characteristics of and factors that influenced the attention network for COVID-19 from January 9, 2020, to April 15, 2020. The study found that (1) Temporally, the attention in the new coronavirus network showed an upward trend from January 9 to January 29, with the largest increase from January 23 to January 29 and a peak on January 29, and then a slow downward trend. The level of attention in the new coronavirus network was basically flat when comparing January 22 and March 4. (2) Spatially, first, from the perspective of regional differences, the network attention in the eastern and central regions decreased in turn. The network users in the eastern region exhibited the highest attention to the new coronavirus, especially in Guangdong, Shandong, Jiangsu and other provinces and cities. The network attention in Tibet, Xinjiang, Qinghai and Ningxia in the western region was the lowest in terms of the national network attention. Second, from the perspective of interprovincial differences, the attention in the new coronavirus network was highly consistent with the Hu Huanyong line of China\'s population boundary. The east of the Hu Huanyong line is densely populated, and the network showed high concern, mostly ranking at the third to fifth levels. (3) The number of Internet users in the information technology field, the population, and the culture and age characteristics of individuals are important factors that influence the novel coronavirus attention network.

Online social networks like Twitter and Facebook are among the most popular sites on the Internet. Most online social networks involve some specific features, including reciprocity, transitivity and degree heterogeneity. Such networks are so called scale-free networks and have drawn lots of attention in research. The aim of this paper is to develop a novel methodology for directed network embedding within the latent space model (LSM) framework. It is known, the link probability between two individuals may increase as the features of each become similar, which is referred to as homophily attributes. To this end, penalized pair-specific attributes, acting as a distance measure, are introduced to provide with more powerful interpretation and improve link prediction accuracy, named penalized homophily latent space models (PHLSM). The proposed models also involve in-degree heterogeneity of directed scale-free networks by embedding with the popularity scales. We also introduce LASSO-based PHLSM to produce an accurate and sparse model for high-dimensional covariates. We make Bayesian inference using MCMC algorithms. The finite sample performance of the proposed models is evaluated by three benchmark simulation datasets and two real data examples. Our methods are competitive and interpretable, they outperform existing approaches for fitting directed networks.