Inquiry of Modernization Management of Rural Community Self-organizing on the Perspective of Social Work

The current rural community self-organizing of China is closely related with the rural social stability as well as economic and social development. However, the current rural community self-organizing construction falls far behind the requirements of realistic practice all over China, which greatly affects the advancement of the rural modernization of China. On the other hand, social work provides a unique perspective and method to deal with these problems. Its service philosophy of selfservice as well as its humanitarian value and practical working methods provide reality conformity for the intervention into rural community self-organizing, making it conductive to improving the social relations between rural community residents and possible to realize the mutual development of rural community and rural community residents.

Exploring Global Demands for Integrating Social Aspects into Community Healthcare: A Literature Review

Aging and crises like pandemics and climate change are global concerns that affect community environments. These social and natural changes influence people’s health worldwide. Aging impacts human health, including physical and mental aspects, and increases the need for care. Recent crises have affected not only the elderly but also younger populations, necessitating further efforts to develop a systematic community strategy. The goal of such a strategy is to maintain or enhance people’s well-being. As we face aging and crises like pandemics and climate change, it becomes essential to consider health holistically and globally, taking into account the community environment and social determinants without boundaries. The present study aimed to explore the necessary aspects of incorporating social determinants into clinical practice, enabling healthcare providers to view health from a holistic and planetary perspective. This approach facilitates the development of integrated community strategies. The study reviewed literature from PubMed, MEDLINE, and CINAHL databases, focusing on medicine, health, and welfare. An electronic search for English-language articles in peer-reviewed journals was conducted up to July 2024, using search terms such as “holistic health,” “planetary health,” and “social determinants.” Eight articles were identified through the search. After excluding three based on their titles, abstracts, and full texts, five articles were selected. The research focused on three areas: perceiving health in ecosystems, considering health-related policy in clinical situations, and addressing health in primary care settings. This study emphasizes the need for further research on innovative, integrated community strategies in the context of a globally aging society, focusing on non-medical aspects like pandemics, climate change, and social determinants to achieve a holistic and planetary understanding of people’s health. It suggests that understanding the social aspects of ecosystems in clinical settings, through interdisciplinary collaboration, is crucial for developing systematic community strategies for people’s well-being life in medical, health, and welfare contexts.

The social determinants of health influencing obesity for the aged in the Pakpoon community context:A qualitative study

Objective:This study aimed to describe the social determinants of health influencing obesity for the aged in a community context and based on the perspectives of various stakeholders.Methods:This was qualitative content analysis study using data from the focus group,individual in-depth interview,and observation.The study population was domiciled in Pakpoon Village,Mung Dis-trict,Nakhon Si Thammarat Province,a tight-knit settlement typical of most retirement communities.Data were collected through two focus group discussions,direct observation,and in-depth interviews with 19 participants.Respondents represented key community groups:local nurses and public health officers,elderly residents,family caregivers(family members),and village health volunteers.Results:The participants shared similar perspectives about the social determinants of health influencing obesity in the aged,which spanned three themes.These were:1)neighborhood food environment(easy access to unhealthy food,no choice to recruit healthy food);2)social networks influencing obesity(family affects food choices and prohibitions on exercise;belief,and socially imposed body image per-ceptions contributing to obesity in the aged);and 3)knowledge,attitudes,and beliefs behind lifestyle choices that cause obesity in the elderly(lack of awareness,personal attitudes,job and familial duties as barriers to engaging in physical activities;over-consumption behaviors lead to obesity in older people).Conclusion:These three themes were the root causes of obesity in the elderly in Pakpoon’s retirement community.This finding suggests that policymakers and nurses can create healthy environments,both to treat and prevent obesity,by raising awareness in younger generations,providing aging the provision of healthy food choices for older adults,encouraging health care professionals to share knowledge,and by modifying the attitudes and beliefs of both caregivers and older adults.

Social and Economic Considerations for Creating Sustainable Climate Change Haven Communities

As Climate Change Haven Communities are constructed across the Northern Hemisphere, it will be necessary to attract two types of migrants to populate them. The first group consists of professionals and companies in eco-sustainable businesses, such as law firms, insurance companies, investment firms, banking, technological innovation, mass media, medical research and pharmaceutical research. The second group will consist of persons engaged in organic/eco-sustainable agriculture whose crops and animal husbandry practices can be transferred successfully to Climate Change Haven regions. The present research focuses on the social and economic variables that must be taken into account to insure that each new Climate Change Haven Community becomes successfully integrated with the local population and forms a cohesive, harmonious social structure. Examples are given from the United States, France, Spain, Portugal and Italy.

Understanding the factors influencing user intention to continue contributing knowledge in social Q&A communities

Purpose:A social question & answer(SQA) community's long-term sustainability depends on its members' willingness to stay and contribute their knowledge continuously in the community.This research aims to investigate the critical factors which influence users' intention to continue contributing knowledge in the SQA community.Design/methodology/approach:Grounded on information systems(IS) continuance theory,this study put forward a model of the factors that influence SQA community members' intention to continue contributing knowledge.Survey was conducted to gather data from knowledge contributors of four major Chinese SQA communities(Baidu Knows,Sina iAsk,Soso Ask and Yahoo! Knowledge).By using the partial least squares(PLS) technique,research hypotheses derived from the proposed model were empirically validated.Findings:Except enjoyment in helping others and knowledge self-efficacy,all other factors including extrinsic reward,reputation enhancement,realization of self-worth,perceived usefulness,attitude towards knowledge contribution,and satisfaction exert significant impacts on users' continuance intentions in an SQA community.Research limitations:First,important factors such as the ease of use of information systems which may influence users' continuance intentions were not investigated in the study.Second,the study sample needs to be enlarged,and users of smaller SQA communities should also be included,to make the results more representative.Practical implications:This study will help SQA community designers and managers develop or improve incentive mechanisms to attract more people to contribute their knowledge and promote the development of the SQA community.Originality/value:This study improves the previous research models and puts forward a model of user continuance intention to contribute knowledge in an SQA community.It will extend the understanding of SQA community users' intention to continue contributing knowledge by distinguishing these users' different roles and focusing only on knowledge contributors.

Analysis of the Current Situation and Influencing Factors of Social Isolation Among the Elderly in the Community

Objective: To investigate the current situation of social isolation among the elderly in the community, and to analyze its influencing factors. Methods: A total of 265 elderly people were selected to conduct the survey using the general information questionnaire and the Chinese version of the social isolation scale for the elderly. Results: The social isolation score of the elderly was (20.15 ± 0.23). Factors such as age, education level, economic status, and social participation ability influenced the social isolation score (P < 0.05). Conclusion: The social isolation of the elderly is more serious, and the social isolation can be alleviated by improving the level of education and the economic situation and strengthening social participation.

Why Do the Imaginary and Imaginary Communities Emerge in Social Theory? National Imaginary in the Context of Globalization

The end of modernism questions reality and its theoretical description,and various attempts of postmodern rethinking of the social emerge-from denial,assertion of the disappearance of the social to its salvation through radical rethinking.Theorizing around the imaginary emerges and continues as a result of this rethinking.Cornelius Castoriadis,for example,absolutizes the concept of the imaginary,which,in his opinion,even contains the rational.Charles Taylor gives imaginary,though important,but limited role as a background knowledge.Speaking of the imaginary,one cannot,of course,ignore Benedict Andersen’s imaginary communities.According to Andersen,the“imagination”of a nation,like any other community,reflects not the fact that they are“invented”or“constructed”but that they are the result of human practice,that social reality is a socio-historical and cultural product.Nation differs from other communities in the style of representation,namely,the representation-understanding,first of all,of space and time.A specific moment in time is connected not only with the past and future,but also with the same moment in another time and space measurement.People in this case,communicate and socialize through books,newspapers,and national languages.Most importantly,the nation as an imaginary community opposes itself to other communities,distinguishes itself from them,and strives for autonomy.And the guarantee of autonomy is the sovereign state,the nation-state,therefore the nation is always connected with the state and the territory of the exercise of its monopoly right.That is,the nation is an imaginary community that is real only to the extent that it is correlated with the modern territorial state.According to the author,the transformation of the national imaginary under the conditions of globalization is characterized by the loss of attachment to the territory,by the fact that territoriality ceases to be the main,organizing principle of social life.Social practices are increasingly formed beyond borders,belonging to ethnicity,national identity is not determined by territory and citizenship.Despite this,we must not forget that globalization is not a finished project.The transformation of the national imaginary should be viewed not only as the emergence of new imaginary communities,whether national or transnational,but also against the backdrop of interaction and even struggle between traditional forms of social practices and new ones,as evidenced by the growth of ethnic conflicts and separatist movements.According to Appudurai,this is also a consequence of globalization processes.And how this confrontation will end,the question remains open.

The Relationship Between Social Isolation, Psychological Resilience, and Psychological Well- Being Among Older People in the Community

Objective:To explore the relationship between social isolation,psychological resilience,and psychological well-being in community-dwelling older adults.Methods:A questionnaire survey was conducted with 265 community-dwelling older adults using the Social Isolation Scale for the Elderly(C-SIS),the 10-item Brief Psychological Resilience Scale,and the Comprehensive Happiness Questionnaire(MHQ).The results were statistically analyzed using SPSS 27.0.Results:The highest score on the Social Isolation Scale for Community Elderly was 23,with a mean entry score of 2.36±0.62.A score of 14 was the cut-off point,with scores of≤14 classified as social isolation.There were 136 cases with scores below 14,resulting in a social isolation incidence rate of 51.3%.The median(P50)psychological resilience score was 27,indicating a higher level of resilience.The total score on the Psychological Well-being Scale was 161,suggesting a moderate to slightly higher level of well-being.Social isolation had a direct negative effect on psychological well-being,while psychological resilience had a positive effect.Conclusion:Older adults should be supported in reducing the incidence of social isolation and increasing psychological resilience to enhance psychological well-being and promote successful aging.

The Relationship Between Social Isolation and Psychological Well-Being Among Older Adults in the Community

Objective:To investigate the psychological well-being of the elderly in Baoding City,Hebei Province,and analyze its influencing factors,with a focus on exploring the relationship between social isolation and psychological well-being.This study aims to provide a reference for effective interventions that promote the physical and mental health of elderly individuals in the community.Methods:A total of 265 elderly individuals from six communities in Baoding City,Hebei Province were surveyed between November 2023 and March 2024 using the general information questionnaire,the Social Isolation Scale for the Elderly,and the Comprehensive Happiness Questionnaire.Results:The total score of the Social Isolation Scale for the elderly in the community was(14.15±3.73)points,indicating a moderate level of social isolation.The average score of P50 on the Psychological Well-being Scale was 4.88,suggesting that the psychological well-being of the elderly in the community was moderate to high.Multivariate regression analysis showed that the level of social isolation significantly influenced the psychological well-being of the elderly(P<0.05),with social isolation negatively correlated with psychological well-being.Conclusion:Healthcare professionals should pay attention to the social isolation of elderly individuals in the community and develop targeted interventions to improve their psychological well-being and quality of life.

Optimization and Innovation of the Operation Model of Mobile Social E-commerce under AI Empowerment:Taking the Female Community Platform“Little Red Book”as an Example

This article takes the female community platform“Little Red Book”as an example to explore the optimization and innovation of mobile community e-commerce operation mode under Artificial Intelligence(AI)empowerment.Firstly,the relevant concepts were defined,and then the unique attributes of mobile community e-commerce were analyzed.As a typical representative of mobile community e-commerce,Little Red Book introduces the background and characteristics of its platform,analyzes its mobile community operation mode,and focuses on exploring how to establish a mobile community e-commerce platform and effective operation mode under the empowerment of AI technology,to provide some reference and inspiration for the development and operation of Little Red Book and other e-commerce platform enterprises.

Correlation between social support and depression in elderly stroke patients in the sequelae stage from five communities of Shanghai, China

Using a convenience sampling method, 81 aged patients who were between 6 and 24 months post-stroke were selected from five communities of Shanghai, China. The correlations between social support and depression, as well as other influential factors, were investigated. Results revealed that 46% （37/81） of the stroke patients suffered from depression. Depression was correlated with social support total scores and the two domains of subjective support and utilization. Older age, male gender, low income, absence of spouse and cerebral hemorrhage were risk factors for depression and identify more vulnerable groups.

Community Workers’Social Support and Sleep Quality during the Coronavirus Disease 2019(COVID-19):A Moderated Mediation Model

To explore the relationship between social support and sleep quality of community workers in Wuhan during the coronavirus disease 2019(the COVID-19 infection epidemic),this research constructed a mediating effect model to explore the mediating psychological mechanism of social support influencing sleep quality of front-line community workers.A total of 500 front-line community workers in Wuhan were investigated.We used the perceived social support scale(PSSS),the Connor-Davidson Resilience Scale(CD-RISC),the perceived stress scale(PSS),and the Pittsburgh sleep quality index(PSQI)to measure social support,psychological resilience,perceived stress and sleep quality.Specifically,the higher the PSQI,the worse the sleep quality.Pearson correlation structural equation model was used to analyze the relationship between these factors.The results showed that:(1)There was a significant negative correlation between social support,psychological resilience,and perceived stress of community workers and PSQI,that means,the higher the level of social support,psychological resilience,and perceived stress,the higher the sleep quality.(2)Social support positively predicted psychological resilience and perceived stress,and perceived stress negatively predicted PSQI.(3)Social support can affect sleep quality through the mediating role of psychological resilience and perceived stress,and the mediating role includes two paths:the single mediating role of perceived stress and the chain mediating role of psychological resilience-perceived stress.(4)Gender moderates the relation-ship between social support and perceived stress,and the influence of social support on perceived stress of women is higher than that of men.Gender moderates the relationship between psychological resilience and PSQI,and only women’s psychological resilience had a negatively predictive effect on PSQI,while men did not,which means that psychological resilience of female frontline community workers can positively predict sleep quality.This research reveals the relationship between social support and sleep quality and its mechanism and verifies that social support can indirectly affect physical health through psychological resilience and perceived stress.It provides reference suggestions and intervention guidance for improving the sleep quality of community workers.

Quantitative classification and analysis on plant communities in the middle reaches of the Tarim River

Plant communities were sampled in the lower reaches of the Tarim River, Xinjiang. The results showed that there are 23 species belonging to 21 genera in 11 families, most of which have low occurrence frequency in quadrats. The most common species is Tamarix ramosissima, which occurred in 17 sites accounting for 89.47% of the total 19 sites. Quantitative classification (TWINSPAN) and ordination (CCA) methods were used to study the distribution patterns of 23 plant species in 19 sites in this valley. TWINSPAN results showed that the plant communities in the middle reaches of the Tarim River could be divided into 3 groups and the sampling sites could be divided into 7 types in 3 groups. CCA results were consistent with TWINSPAN results, and showed species distribution patterns correlated with major environmental variables of groundwater level and soil moisture.

A Genetic Algorithm for Identifying Overlapping Communities in Social Networks Using an Optimized Search Space

There are currently many approaches to identify the community structure of a network, but relatively few specific to detect overlapping community structures. Likewise, there are few networks with ground truth overlapping nodes. For this reason,we introduce a new network, Pilgrim, with known overlapping nodes, and a new genetic algorithm for detecting such nodes. Pilgrim is comprised of a variety of structures including two communities with dense overlap,which is common in real social structures. This study initially explores the potential of the community detection algorithm LabelRank for consistent overlap detection;however, the deterministic nature of this algorithm restricts it to very few candidate solutions. Therefore, we propose a genetic algorithm using a restricted edge-based clustering technique to detect overlapping communities by maximizing an efficient overlapping modularity function. The proposed restriction to the edge-based representation precludes the possibility of disjoint communities, thereby, dramatically reducing the search space and decreasing the number of generations required to produce an optimal solution. A tunable parameterr allows the strictness of the definition of overlap to be adjusted allowing for refinement in the number of identified overlapping nodes. Our method, tested on several real social networks, yields results comparable to the most effective overlapping community detection algorithms to date.

Identifying influential nodes in social networks via community structure and influence distribution difference

This paper aims to effectively solve the problem of the influence maximization in social networks.For this purpose,an influence maximization method that can identify influential nodes via the community structure and the influence distribution difference is proposed.Firstly,the network embedding-based community detection approach is developed,by which the social network is divided into several high-quality communities.Secondly,the solution of influence maximization is composed of the candidate stage and the greedy stage.The candidate stage is to select candidate nodes from the interior and the boundary of each community using a heuristic algorithm,and the greedy stage is to determine seed nodes with the largest marginal influence increment from the candidate set through the sub-modular property-based Greedy algorithm.Finally,experimental results demonstrate the superiority of the proposed method compared with existing methods,from which one can further find that our work can achieve a good tradeoff between the influence spread and the running time.

Graph Transformer for Communities Detection in Social Networks

Graphs are used in various disciplines such as telecommunication,biological networks,as well as social networks.In large-scale networks,it is challenging to detect the communities by learning the distinct properties of the graph.As deep learning hasmade contributions in a variety of domains,we try to use deep learning techniques to mine the knowledge from large-scale graph networks.In this paper,we aim to provide a strategy for detecting communities using deep autoencoders and obtain generic neural attention to graphs.The advantages of neural attention are widely seen in the field of NLP and computer vision,which has low computational complexity for large-scale graphs.The contributions of the paper are summarized as follows.Firstly,a transformer is utilized to downsample the first-order proximities of the graph into a latent space,which can result in the structural properties and eventually assist in detecting the communities.Secondly,the fine-tuning task is conducted by tuning variant hyperparameters cautiously,which is applied to multiple social networks(Facebook and Twitch).Furthermore,the objective function(crossentropy)is tuned by L0 regularization.Lastly,the reconstructed model forms communities that present the relationship between the groups.The proposed robust model provides good generalization and is applicable to obtaining not only the community structures in social networks but also the node classification.The proposed graph-transformer shows advanced performance on the social networks with the average NMIs of 0.67±0.04,0.198±0.02,0.228±0.02,and 0.68±0.03 on Wikipedia crocodiles,Github Developers,Twitch England,and Facebook Page-Page networks,respectively.

The influence of marital status on the social dysfunction of schizophrenia patients in community

Objective:Estimate predictive associations of marital status with social dysfunction in schizophrenia patients.Methods:817 schizophrenia patients lived in the community of Dongguan,Guangdong province,China,were investigated with the Social Disability Screening Schedule(SDSS)during a three-month period(1.2010e3.2010).The demographic data were harvested.The c2 test,t test,and fisher's exact were used for comparisons between groups,as appropriate.Multinomial logistic regression(MLR)was used to analyze the predictive associations of demographic variables to the grading of social dysfunctions.Results:The study group consisted of male and female patients aged 16e59 years,407 females,and 410 males with the mean age(40.7±9.5)years.Analysis of the data revealed significant differences in course of disease and marital status among patients(with and without dysfunction).The married patient made a significant difference with divorced/widowed patient in mildlyemoderately social dysfunction.There was a significant difference in married and never-married patient with mildly and profoundly social dysfunction.Significant differences were noticed in the self care and occupational roles of the married patient with that of the never-married.Conclusion:This study confirmed that bad marital status is associated with higher odds of social dysfunction among patients with schizophrenia living in the community.These effects should be included in considerations of public health investments in preventing and treating mental disorders.

Community Discovery with Location-Interaction Disparity in Mobile Social Networks

With the fast-growth of mobile social network, people＇ s interactions are frequently marked with location information, such as longitude and latitude of visited base station. This boom of data has led to considerable interest in research fields such as user behavior mining, trajectory discovery and social demographics. However, there is little research on community discovery in mobile social networks, and this is the problem this work tackles with. In this work, we take advantage of one simple property that people in different locations often belong to different social circles in order to discover communities in these networks. Based on this property, which we referred to as Location-lnteraction Disparity （LID）, we proposed a state network and then define a quality function evaluating community detection results. We also propose a hybrid community- detection algorithm using LID tor discovering location-based communities effectively and efficiently. Experiments on synthesis networks show that this algorithm can run effectively in time and discover communities with high precision. In realworld networks, the method reveals people＇s different social circles in different places with high efficiency.

Advanced Community Identification Model for Social Networks

Community detection in social networks is a hard problem because of the size,and the need of a deep understanding of network structure and functions.While several methods with significant effort in this direction have been devised,an outstanding open problem is the unknown number of communities,it is generally believed that the role of influential nodes that are surrounded by neighbors is very important.In addition,the similarity among nodes inside the same cluster is greater than among nodes from other clusters.Lately,the global and local methods of community detection have been getting more attention.Therefore,in this study,we propose an advanced communitydetection model for social networks in order to identify network communities based on global and local information.Our proposed model initially detects the most influential nodes by using an Eigen score then performs local expansion powered by label propagation.This process is conducted with the same color till nodes reach maximum similarity.Finally,the communities are formed,and a clear community graph is displayed to the user.Our proposed model is completely parameter-free,and therefore,no prior information is required,such as the number of communities,etc.We perform simulations and experiments using well-known synthetic and real network benchmarks,and compare them with well-known state-of-the-art models.The results prove that our model is efficient in all aspects,because it quickly identifies communities in the network.Moreover,it can easily be used for friendship recommendations or in business recommendation systems.

Set pair three-way overlapping community discovery algorithm for weighted social internet of things

There are many problems in Social Internet of Things(IoTs),such as complex topology information,different degree of association between nodes and overlapping communities.The idea of set pair information grain computing and clustering is introduced to solve the above problems so as to accurately describe the similarity between nodes and fully explore the multi-community structure.A Set Pair Three-Way Overlapping Community Discovery Algorithm for Weighted Social Internet of Things(WSIoT-SPTOCD)is proposed.In the local network structure,which fully considers the topological information between nodes,the set pair connection degree is used to analyze the identity,difference and reverse of neighbor nodes.The similarity degree of different neighbor nodes is defined from network edge weight and node degree,and the similarity measurement method of set pair between nodes based on the local information structure is proposed.According to the number of nodes'neighbors and the connection degree of adjacent edges,the clustering intensity of nodes is defined,and an improved algorithm for initial value selection of k-means is proposed.The nodes are allocated according to the set pair similarity between nodes and different communities.Three-way community structures composed of a positive domain,boundary domain and negative domain are generated iteratively.Next,the overlapping node set is generated according to the calculation results of community node membership.Finally,experiments are carried out on artificial networks and real networks.The results show that WSIoT-SPTOCD performs well in terms of standardized mutual information,overlapping community modularity and F1.