Government-Nongovernmental Organization (NGO) Collaboration in Macao's COVID-19 Vaccine Promotion: Social Media Case Study

BACKGROUND

The COVID-19 pandemic triggered unprecedented global vaccination efforts, with social media being a popular tool for vaccine promotion.

OBJECTIVE

This study probes into Macao's COVID-19 vaccine communication dynamics, with a focus on the multifaceted impacts of government agendas on social media.

METHODS

We scrutinized 22,986 vaccine-related Facebook posts from January 2020 to August 2022 in Macao. Using automated content analysis and advanced statistical methods, we unveiled intricate agenda dynamics between government and nongovernment entities.

RESULTS

"Vaccine importance" and "COVID-19 risk" were the most prominent topics co-occurring in the overall vaccine communication. The government tended to emphasize "COVID-19 risk" and "vaccine effectiveness," while regular users prioritized vaccine safety and distribution, indicating a discrepancy in these agendas. Nonetheless, the government has limited impact on regular users in the aspects of vaccine importance, accessibility, affordability, and trust in experts. The agendas of government and nongovernment users intertwined, illustrating complex interactions.

CONCLUSIONS

This study reveals the influence of government agendas on public discourse, impacting environmental awareness, public health education, and the social dynamics of inclusive communication during health crises. Inclusive strategies, accommodating public concerns, and involving diverse stakeholders are paramount for effective social media communication during health crises.

Spatial association network of PM2.5 and its influencing factors in the Beijing-Tianjin-Hebei urban agglomeration

In this paper, we empirically study the spatial association network of PM_2.5 and the factors influencing those correlations using the gravity model, social network analysis (SNA), and the quadratic assignment procedure (QAP) based on data from the Beijing-Tianjin-Hebei urban agglomeration (BTHUA) in China from 2005 to 2018. We draw the following conclusions. First, the spatial association network of PM_2.5 exhibits relatively typical network structure characteristics: the network density and network correlations are highly sensitive to efforts to control air pollution, and there are obvious spatial correlations within the network. Second, cities in the center of the BTHUA have large network centrality values, while cities in the peripheral region have small centrality values. Tianjin is a core city in the network, and the spillover effect of PM_2.5 pollution in Shijiazhuang and Hengshui is the most noticeable. Third, the 14 cities can be divided into four plates, with each plate having obvious geographical location characteristics and linkage effects. The cities in the association network are divided into three tiers. Beijing, Tianjin, and Shijiazhuang are located in the first tier, and a considerable number of PM_2.5 connections are completed through these cities. Fourth, differences in geographical distance and urbanization are the main drivers of the spatial correlations of PM_2.5. The greater the urbanization differences, the more likely the generation of PM_2.5 links is, while the opposite is true for differences in geographical distance.

Triple Alignment: Congruency of Perceived Preschool Classroom Social Networks Among Teachers, Children, and Researchers

Classroom social networks are influential to young children's cognitive, social-emotional, and language development, but assessment and analyses of social networks are complex. Findings have been mixed regarding whether different informants (teachers, children, researchers) are congruent in perceiving classroom social networks. There is also a lack of discussion about the roles of network transformation (converting value networks into binary networks), a required data step for widely used statistical network analyses. This study addressed these issues based on network data of 16 preschool children containing 240 potential dyadic interactions collected from teacher ratings, child nominations, and researcher observations across 44 observation cycles over four school days. Results showed that the three informants were congruent in perceiving the classroom social network, whereas the level of congruency between the teacher-report and the researcher-report networks was the highest. Binary transformation of social networks tended to decrease the level of congruency across informants, although the level of congruency tended to be higher when more stringent binary transformation thresholds were selected.

Genetic, spatial, and social relationships among adults in a group of howler monkeys (Alouatta palliata) from Barro Colorado Island, Panama

Kinship plays an important role in the social behavior of many primate species, including patterns of intra-group affiliation and cooperation. Within social groups, kinship is strongly affected by dispersal patterns, with the degree of relatedness among group-mates expected to decrease as the tendency to disperse increases. In primate species characterized by bisexual dispersal, relatedness among adult group-mates is predicted to be low, with social interactions shaped largely by factors other than kinship. To date, however, few studies have examined the role of kinship in social interactions in bisexually dispersing species. Accordingly, we collected genetic, spatial and behavioral data on all adult members (three males, six females) in a group of free-ranging mantled howler monkeys (Alouatta palliata)--a bisexually dispersing species of atelid primate--from Barro Colorado Island (BCI), Panama. Analyses of microsatellite variation revealed that relatedness was greater among adult males in this group (mean pairwise relatedness = 0.32 for males versus 0.09 for females). Relatedness among individuals, however, was not associated with either spatial proximity or frequency of social interactions. Instead, sex was a better predictor of both of these aspects of social behavior. While relatedness among adults had no discernible effect on the intra-group social interactions documented in this study, we postulate that kinship may facilitate affiliative and cooperative behaviors among male group-mates when interacting competitively with neighboring howler groups over access to food or potential mates.

Sequential Monte Carlo for Maximum Weight Subgraphs with Application to Solving Image Jigsaw Puzzles

We consider a problem of finding maximum weight subgraphs (MWS) that satisfy hard constraints in a weighted graph. The constraints specify the graph nodes that must belong to the solution as well as mutual exclusions of graph nodes, i.e., pairs of nodes that cannot belong to the same solution. Our main contribution is a novel inference approach for solving this problem in a sequential monte carlo (SMC) sampling framework. Usually in an SMC framework there is a natural ordering of the states of the samples. The order typically depends on observations about the states or on the annealing setup used. In many applications (e.g., image jigsaw puzzle problems), all observations (e.g., puzzle pieces) are given at once and it is hard to define a natural ordering. Therefore, we relax the assumption of having ordered observations about states and propose a novel SMC algorithm for obtaining maximum a posteriori estimate of a high-dimensional posterior distribution. This is achieved by exploring different orders of states and selecting the most informative permutations in each step of the sampling. Our experimental results demonstrate that the proposed inference framework significantly outperforms loopy belief propagation in solving the image jigsaw puzzle problem. In particular, our inference quadruples the accuracy of the puzzle assembly compared to that of loopy belief propagation.