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.

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.

An Extended Fuzzy-DEMATEL System for Factor Analyses on Social Capital Selection in the Renovation of Old Residential Communities

China has been promoting the renovation of old residential communities vigorously.Due to the financial pressure of the government and the sustainability of the renovation of old residential communities,public-private partnerships(PPP)have already gained attention.The selection of social capital is key to improving the efficiency of the PPP model in renovating old residential communities.In order to determine the influencing factors of social capital selection in the renovation of old residential communities,this paper aims to find an effective approach and analyze these factors.In this paper,a fuzzy decision-making and trial evaluation laboratory(fuzzy-DEMATEL)technique is extended and amore suitable systemis developed for the selection of social capital using the existing group decisionmaking theory.In the first stage,grounded theory is used to extract the unabridged key influencing factors for social capital selection in the renovation of old residential communities.Secondly,by considering the impact of expert weights,the key influencing factors are identified.The interactions within these influencing factors are discussed and the credibility of the results is verified by sensitivity analysis.Finally,these key influencing factors are sorted by importance.Based on the results,the government should focus on a technical level,organizationalmanagement abilities,corporate reputation,credit status,etc.This study provides the government with a theoretical basis and a methodology for evaluating social capital selection.

Application of Social Media Tool in Disaster Management in Disaster-Prone Communities in Freetown, Sierra Leone

This study used both the “digital divide” and “attribution theory” to analyze the propensity of social media use by disaster-prone communities. The study focused on the variables that may affect how social media is used for disaster management. Structural equation modeling (SEM) was utilized in the study to analyze the data and test the hypotheses after using a survey questionnaire to collect the data. The study’s findings show that: 1) communities that are vulnerable to disasters are less likely to use social media for disaster management, 2) personal effort and intention to use social media for disaster management are positively correlated, and 3) task complexity and intention to use social media for disaster management are negatively correlated. The study added to the body of knowledge regarding the role social media plays in disaster management.

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.

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.

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 Communities Using IID for a Multilayer Networks

In online social networks(OSN),they generate several specific user activities daily,corresponding to the billions of data points shared.However,although users exhibit significant interest in social media,they are uninterested in the content,discussions,or opinions available on certain sites.Therefore,this study aims to identify influential communities and understand user behavior across networks in the information diffusion process.Social media platforms,such as Facebook and Twitter,extract data to analyze the information diffusion process,based on which they cascade information among the individuals in the network.Therefore,this study proposes an influential information diffusion model that identifies influential communities across these two social media sites.More-over,it addresses site migration by visualizing a set of overlapping communities using hyper-edge detection.Thus,the overlapping community structure is used to identify similar communities with identical user interests.Furthermore,the com-munity structure helps in determining the node activation and user influence from the information cascade model.Finally,the Fraction of Intra/Inter-Layer(FIL)dif-fusion score is used to evaluate the efficiency of the influential information diffu-sion model by analyzing the trending influential communities in a multilayer network.However,from the experimental result,it observes that the FIL diffusion score for the proposed method achieves better results in terms of accuracy,preci-sion,recall and efficiency of community detection than the existing methods.

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 Factors of Collective Intelligence Emergence in Knowledge Communities Based on Social Network Analysis

The advent of the age of Information shifts the environment we live in from off-line to on-line. The prospect of Collective Intelligence (CI) is promising. Based on this background, the aim of this paper is to discover the emergence mechanism and influence factors of CI in knowledge communities using the method of quantitative and qualitative analysis. On the basis of the previous research work, our model theorizes that the two dimensions of social network (i.e., interactive network structure and participant’s characteristics) affect two references of effectiveness (i.e. group knowledge production and participation of group decision). And this hypothetical model is validated with simulation data from “Zhihu” community. Our model has been useful since it offers some inspirations and directions to promote the level of CI in knowledge communities.

An indicator-based approach to assess village-level social and biophysical vulnerability of agriculture communities in Uttarakhand,India

With the growing recognition to myriad forms of current and future threats in the mountain agriculture systems,there is a pressing need to holistically understand the vulnerability of mountain agriculture communities.The study aims to assess the biophysical and social vulnerability of agriculture communities using an indicator-based approach for the state of Uttarakhand,India.A total of 14 indicators were used to capture biophysical vulnerability and 22 for social vulnerability profiles of15285 villages.Vulnerability analysis was done at village level with weights assigned to each indicator using Analytical Hierarchical Process(AHP).The results of the study highlight the presence of very high biophysical vulnerability(0.82 ± 0.10) and high social vulnerability(0.65 ± 0.15) within the state.Based on the results,it was found that incidences of high biophysical vulnerability coincide with presence of intensified agriculture land and absence of dense forest.Higher social vulnerability scores were found in villages with an absence of local institutions(like Self Helping Groups(SHGs)),negligible infrastructure facilities and higher occupational dependence on agriculture.A contrast was observed in the vulnerability scores of villages present in the three different altitudinal zones in the study area,indicating respective vulnerability generating conditions existing in these three zones.Biophysical vulnerability was recorded to be highest in the villages falling in the lower zone and lowest in the upper zone villages;whereas,social vulnerability was found to be highest in the middle zone villages and lowest in lower zone villages.Our study aids policy makers in identifying areas for intervention to expedite agriculture adaptation planning in the state.Additionally,the adaptation programmes in the region need to be more context-specific to accommodate the differential altitudinal vulnerability profiles.

Enhancing Data Forwarding Efficiency in SIoT with Multidimensional Social Relations

Effective data communication is a crucial aspect of the Social Internet of Things(SIoT)and continues to be a significant research focus.This paper proposes a data forwarding algorithm based on Multidimensional Social Relations(MSRR)in SIoT to solve this problem.The proposed algorithm separates message forwarding into intra-and cross-community forwarding by analyzing interest traits and social connections among nodes.Three new metrics are defined:the intensity of node social relationships,node activity,and community connectivity.Within the community,messages are sent by determining which node is most similar to the sender by weighing the strength of social connections and node activity.When a node performs cross-community forwarding,the message is forwarded to the most reasonable relay community by measuring the node activity and the connection between communities.The proposed algorithm was compared to three existing routing algorithms in simulation experiments.Results indicate that the proposed algorithmsubstantially improves message delivery efficiency while lessening network overhead and enhancing connectivity and coordination in the SIoT context.

ComRank： Joint Weight Technique for the Identification of Influential Communities

Recently, the community analysis has seen enormous research advancements in the field of social networks. A large amount of the current studies put forward different models and algorithms about most influential people. However, there is little work to shed light on how to rank communities while considering their levels that are determined by the quality of their published contents. In this paper, we propose solution for measuring the influence of communities and ranking them by considering joint weight composed of internal and external influence of communities. To address this issue, we design a novel algorithm called Com Rank: a modification of Page Rank, which considers the joint weight in order to identify impact of each community and ranking them. We use real-world data trace in citation network and perform extensive experiments to evaluate our proposed algorithm. The comparative results depict significant improvements by our algorithm in community ranking due to the inclusion of proposed weighting feature.

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.

Contextualized Analysis of Social Networks:Collaboration in Scientific Communities

Currently, the collaboration in scientific communities has been studied in order to explain, among other things, the knowledge diffusion. The quality of Graduate Programmes is often associated with the scientific collaboration. This paper discusses how scientific collaboration processes can be identified and characterized through social and complex networks. For this purpose, collaboration networks of bibliographic production, research projects, and committees of PhD theses and Masters’ dissertations by researchers from a graduate program in computational modeling were studied. The data were obtained from CAPES’ reports of the period from 2001 to 2009. Among the studied indices, centrality indices indicate the presence of prominent researchers who influence others and promptly interact with other researchers in the network. The indices of complex networks reveal the presence of the small-world (i.e. these networks are favorable to increase coordination between researchers) phenomenon and indicate a behavior of scale-free degree distribution (i.e. some researchers promote clustering more than others) for one of the studied networks.

Human Security, Poverty Pattern and Social Order in Igbo Rural Communities of Contemporary Nigeria

The Igbo have their homeland in seven states of Nigeria mainly Imo, Abia, Anambra, Ebonyi, Delta and Rivers. They are receptible to new ideas and adapt easily to change. The ramifications of human insecurity, poverty, social disorder, poor coherence and poor integration appear to haunt them and the gravity is felt more in the rural communities. The factors are traceable to many pathetic issues. The pathological consequences do affect Igbo stability and navigation in the Nigerian socio-economic environment. The causality constitutes the physical, human, natural, financial and social assets. It is recommended, among others, that the people should return to core values and norms, stick to their own noble identities, have a framework for tackling insecurity and hunger, target the youth in poverty reduction measures and tackle the herdsmen menace. Equally, the abused philosophies used to support dangerous and strange behavior should be tackled.

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.

Corporate Social Responsibility Projects by Transnational Oil Corporations in Nigerian Niger Delta Region： The Experiences of Selected Oil Producing Communities

A well-known fact about the Nigerian Niger Delta region is incessant conflicts between the oil transnational corporations （Oil TNCs） and the oil producing communities. This could be attributed to the fact that the activities of Oil TNCs have continued to unleash untold devastation on the environment of the oil producing communities and its consequences on the local economy and by extension the total obliteration of the livelihood of the inhabitants of the area. Therefore, the Oil TNCs are increasingly becoming conscious of their devastating impact on the ecology of the area and their blatant disregard for the socio-economic development of the host communities. Consequently, the Oil TNCs have come to embrace the idea of executing Corporate Social Responsibility （CSR） projects as a vehicle to intervene meaningfully in order to mitigate the adverse effect of their operations in host communities. This paper attempts a review and analysis of CSR practices of the two major Oil TNCs in Bayelsa State： Shell and Agip in six host communities： Olugboboro, Olugbobiri, Ikebiri 1, Oporoma, Angiama, and Peremabiri in Southern ljaw local government area. The key question explored in this study is： Has the practice of CSR in the Nigerian Niger Delta region by Oil TNCs brought about socio-economic development and drastic reduction in conflict between the host communities and the Oil TNCs？ The paper argues that CSR projects of transnational oil corporations in Nigeria are driven by short-term expediency rather than the long term development needs of host communities through the provision of poor quality social amenities to these communities in order to secure social license to operate. For transnational oil corporations to make positive impact in the Nigerian Niger Delta Region, their CSR projects should be long tern in nature, taking into consideration the sustainable development needs of the local communities. The CSR projects should be in the form of high quality social amenities and environmental rehabilitation and protection, which could serve the needs of the present and future generations.

Social Effects of Hearing Loss on Patients in Jos, North Central Nigeria

Hearing loss has caused serious social effects among people living with it. Those who relate to patients with hearing loss (PHL) also share some part of the negative effects. Some specifics are communication disability, which impacts speech and language development, academic performance, and social or work life. In previous years, the problem was predicted to be aggravated as the expected life span of the population increased. The study was conducted among PHL and their family members in JUTH and Kazahyet Audiology Service in Jos. 150 PHL were purposively sampled. The study was guided by a Cross-sectional Survey Research Design, and the specific objectives were to (1) identify the social effects of hearing loss on the PHL, (2) determine the implication of social effects on PHL, and (3) determine the extent at which these social effects affect PHL. The outcome of the study shows that the social effects faced by PHL are poor relationships, no secrets, dependence on sign language, frustration, depression, and dependence on lip reading. Some stop schooling, and others feel laughed at and therefore choose the path of isolation. The implication is that hearing loss is expensive to manage. PHL always feel they are not contributing their quarter in life as usual;they feel stigmatized and are not easy to relate with. The study recommends that the government should come up with policies that will check man-made behaviors that exert negative social effects on PHL in our society, subsidize the cost of hearing aids and cochlear implants to be affordable for PHL, formulate a policy on mandatory newborn hearing screening before the infant is discharged from the hospital to help in the early identification of hearing loss. Finally, the early creation of awareness of the dangers or consequences of hearing loss will go a long way in preventing our society from involvement in high-risk behaviors that will cause hearing loss.