4.1. Intellectual Bases of Community Resilience
The document co-citation network is shown in
Figure 10 using CiteSpace software. The node type was set as a reference in this part. The time slice was set to 2 years, and the top 35 high-cited publications were selected for visual network presentation in each period. Nodes refer to citations in data sources, and links represent co-citations between different documents. The color of the link is consistent with the year color in
Figure 10. For example, the yellow link represents a publication that was jointly referenced in 2019 and 2020. The top 10 highly cited documents in community research, acquired from the statistical results of references cited in 2266 articles, are listed in
Table 7. The review “Community Security as a Metaphor, Theory, Set of Capacities, and Strategy for Disaster Readiness” was cited 244 times, the highest-frequency citation in the community resilience field. This paper believes that resilience and health stem from various adaptive abilities and define them as resources with dynamic attributes. The author combined this view with evidence to provide a better understanding and building community resilience [
40]. The article called “Community Resilience: Towards an Integrated Approach”, published in Society and Natural Resources in 2013, was cited 217 times. This article explored comprehensive methods for constructing community resilience from the background of social-ecological systems, the psychology of development, and mental health. By integrating resilience research across disciplines, it emphasized the use of critical thinking in the construction of comprehensive resilience [
42]. As the third most cited literature, the article “A place-based model for understanding community resilience to natural disasters”, published in 2008, has been cited 164 times. Overall, most of the highly cited documents are summary and commentary papers with a high reference value.
The book “Building Resilience: Social capital in post-disaster recovery”, published in 2012, is the most-read book in community resilience research. Aldrich, the author of this book, examined the post-disaster responses of four distinct communities—Tokyo following the 1923 earthquake, Kobe after the 1995 earthquake, Tamil Nadu after the 2004 Indian Ocean Tsunami, and New Orleans post-Katrina. The book highlighted the critical role of social capital in the ability of a community to withstand disaster and rebuild both the infrastructure and the ties that are at the foundation of any community [
43]. The article “Disaster Resilience Indicators for Benchmarking Baseline Conditions” has the highest centrality, indicating that it plays a crucial role in community resilience research. This article and the article named “A Place-based Model for Understanding Community Resilience to Natural Disasters” were published by the same author: Cutter S.L. Cutter et al. constructed a series of baseline indicators including social resilience, economic resilience, infrastructure resilience, and community resilience to show the spatial resilience distribution at the county level in the southeastern United States [
15]. Additionally, these indicators were extended to three cities to present the comprehensive resilience score at the city level. This paper put forward some specific indicators for resilience assessment and provided a specific method for disaster planners and decision-makers to improve community resilience [
15].
Cluster analysis of highly cited documents was made by CiteSpace software, as shown in
Figure 11. The time slice was set to 2 years, and the top 35 most cited documents were selected for each slice. As the founder and promoter of CiteSpace, Chen Chaomei suggested that 7–10 clusters are more suitable for overall structure distribution and content analysis, with 10 or more members in each cluster [
44]. This is because we will not obtain a big picture if there are many clusters, and we will not also learn much information from the network if there are very few clusters [
45]. Based on the network structure and the clarity of clustering, CiteSpace proposes two indicators: the modularity value and the silhouette value, which can be used as the basis for us to judge the effect of spectrogram drawing [
44]. The ranges of silhouette and modularity values are from 0 to 1. The larger the silhouette, the more perfect the clustering. The silhouette of each cluster should be above 0.7 [
46]. The clustering in this study is based on the goodness of fit between the research content and 9 clusters composed of 10 or more components were obtained (as shown in
Figure 11). The mean silhouette of clusters is 0.8843, and all the silhouette values of each part are above 0.7. Modularity is a crucial parameter to measure the structural characteristics of the overall clustering network [
46]. The modularity of the clustering is 0.8258, and the fitting effect is preferable. After clustering content integration, intellectual bases of community resilience were finally classified into seven classes. It should be noted that Alaska (#1) is a regional amalgamation of studies, and it is not viewed as one of the classes. This is because the studies related to Alaska are included in the following classes.
Class one: Social capital mechanism (#0). This class has the largest area with a silhouette of 0.979 and contains 27 papers. Compared with the previous emphasis on physical resilience, scholars have gradually realized the key role of social capital and its network in disaster recovery. The social capital network of individuals and communities is an important way to obtain various resources in a disaster situation, including information, aid, financial resources, and emotional and psychological support. [
47,
48,
49]. Most of the early studies focused on specific disaster cases and explored the impact of social capital and the presence of networks to call on authorities to consider social capital as a significant aspect of community resilience. In recent years, the role of social capital mechanisms in community resilience-building has become more prominent, and the research has become more in-depth.
Class two: Evolution of Resilience Knowledge (#2 and #4). The silhouettes are 0.986 and 0.914, and the quantities of articles are 21 and 18, respectively. The transfer of resilience knowledge in different disciplines has become a significant knowledge background for current resilience research. In 1973, Holling officially introduced the concept of resilience into the ecosystem for the first time, regarding it as the ability to persist in the face of change [
3]. Subsequently, resilience extended to psychiatry and psychology [
50,
51], laying a good foundation for the research of psychological resilience. After the twentieth century, resilience has gradually been adopted in the fields of ecology, psychology, economics, and engineering. As the idea of resilience gradually attempts to become integrated on the social level, some scholars have proposed that there is a large degree of coupling between social systems and ecosystem resilience construction. Additionally, there are many obvious connections between them, especially those groups and communities that rely on ecology and environmental resources for their livelihoods [
52]. Folke described the emergence of a dynamic perspective of social ecosystems in the construction of resilience. He also proposed establishing an adaptive management method that responds to changes in the ecosystem [
53]. The emergence of the social ecosystem perspective provided a vital resilience analysis framework for later academic circles and enriched the theoretical and practical achievements of resilience research.
Class three: Earthquake resistance and disaster mitigation (#3 and #6). The silhouettes are 0.893 and 0.952, and the number of articles is 19 and 15, respectively. These studies are mainly concentrated in the field of specific disaster risk resilience, especially resilience focusing on specific natural disasters such as earthquakes, volcanic eruptions, floods, tsunamis, and hurricanes. These studies target specific areas for resilience assessment, or target resilience measurement and improvement of a single subsystem, such as electric power systems [
54], medical infrastructure, and economic systems [
55,
56]. The expansion of resilience-building based on specific disaster areas provides a reference for the follow-up practice of communities to resist specific risks.
Class four: Substance abuse group research (#5). The silhouette is 0.982 and contains 15 articles. The early studies on this topic mostly focused on substance abuse by special groups such as African Americans, children, and adolescents [
57,
58]. To improve the resilience of special groups to resist substance abuse, researchers generally use interview-style methods for special groups to discuss measures to build resilience from the perspective of families, communities, schools, and clinics. However, with the changes of the times, the topic has gradually expanded to new groups that have attracted broad attention, such as transgender populations and veterans [
59,
60].
Class five: Rural community resilience development (#7). Its silhouette is 0.987 and it contains 14 papers. With the acceleration of global urbanization, the disappearing rural areas and their weak economy, and declining population make it more urgent to enhance rural resilience. This type of paper focuses on the resilience of rural communities and remote rural areas that respond to specific disaster risks. Through field surveys of people in rural areas, scholars explored the factors that influence the resilience of rural communities, including community members, social, economic, and environmental factors [
61,
62], and put forward suggestions to policymakers to enhance the community’s ability to withstand disasters. This type of study mostly uses empirical methods such as questionnaires and interviews. The research results have strong explanatory power.
Class six: Resilience-building in the least-developed countries (#8). The silhouette of this cluster is 0.968 with 10 articles. The least developed countries have weak anti-risk capabilities in certain areas such as society, economy, politics, and the environment, which have attracted widespread attention from academic circles and international organizations. Countries and regions with weaker climate change resilience are the focus of the international community. International organizations usually establish special funds to enhance regional climate resilience, such as the GLOF Risk Reduction Project of the United Nations Development Program and the Reducing Climate Change-induced Risks and Vulnerabilities from Glacial Lake Outburst Floods in the Punakha-Wangdue and Chamkhar Valleys funded by the Global Environment Facility (Washington, DC, USA) [
63]. Similar research also includes exploring resilient development paths in areas of armed conflict and economically underdeveloped areas [
64,
65]. This type of article mostly conducts case studies in underdeveloped countries and regions to provide different dimensions of resilience-building suggestions for regions with weaker risk resistance.
Class seven: Emergency preparedness (#9). It contains 10 articles with a silhouette of 0.964. Adequate emergency preparedness is viewed as an essential element of disaster response and recovery. Preparing for disasters, such as emergency material storage and evacuation plans, can greatly reduce losses caused by the disaster; with the increasing uncertainty of natural and unnatural disasters, more and more scholars have focused their disaster preparedness on the level of families and special groups. More people realize that in addition to the measures of emergency management departments, the emergency preparedness of individuals and families is also crucial. Emergency preparedness is complex and requires sufficient knowledge, motivation, resources, and education to promote preparations. Furthermore, there is an urgent need to move forward in the direction of focusing on the unique needs of children, the elderly, and people with functional impairments [
66,
67]. This type of research believes that expanding emergency preparedness at the individual and family level to the community level can strengthen community resilience.
4.2. Research Hotspots of Community Resilience
The cluster network mapping of high-frequency keywords was conducted by CiteSpace. The time slice was set to 2 years, and the top 50 high-frequency keywords were extracted to form clusters. The high-frequency keywords were sorted into nine specific clusters, as shown in
Figure 12. The average modularity and silhouette of clustering in
Figure 12 are 0.7075 and 0.8951, respectively. The overall clustering effect is good. Due to the length limit, only the top 30 high-frequency keywords are presented in
Table 8. It was found that excluding the keyword community resilience, the top five high-frequency keywords are vulnerability, climate change, disaster, framework, and adaptation. How to deal with the vulnerability of communities, adapt to climate change, improve the framework for building resilience, and resist various uncertain disaster risks have become the key issues in community resilience. The top 10 high-frequency keywords also include risk, management, recovery, model, and system. After the clustering of high-frequency keywords, knowledge divisions of community resilience research were carried out. Note that the topic of substance abuse (cluster eight) constitutes continuous stresses and requires ongoing community support of families and individuals, but this is not an integral part of the study of community resilience. Therefore, the topic of substance abuse is not viewed as a research hotspot. Finally, all clusters identified by CiteSpace were further summarized into the five hotspots, and detailed analyses were as follows:
Topic one: The concept of resilience (cluster zero and cluster four).
Resilience was first introduced to the field of ecosystems by the ecologist Holling C. and later expanded to sociology. It has experienced a process from engineering resilience to ecological resilience to evolutionary resilience and has become a hot topic of multidisciplinary joint research [
3]. However, this has also led to different interpretations of resilience in different disciplines. Reaching a consensus on these concepts is still an urgent issue facing the academic community. Therefore, many scholars have turned their attention to the sorting out of resilience and related concepts. Folke C. has systematically integrated “resilience”, “adaptability”, and “transformability”. He argued that adaptability represents the capacity to adjust responses to changing external drivers and internal processes and is part of resilience. Transformability is the capacity to cross thresholds into new development trajectories. All three are critical factors influencing the transformation of the social–ecological systems (SES) [
5]. Manyena SB re-examined the role of resilience and vulnerability on the easily confusing problem of the concept of resilience, and explained the relationship between vulnerability and resilience, making the concept of resilience clearer [
11]. With the continuous extension of the concept of resilience, community resilience, as the foundation of urban resilience construction, has become the main direction of community development in many countries today. However, many scholars still misuse and confuse community resilience in community building. By combing and comparing the concepts of community resilience, community institutions, community vulnerability, community adaptability, and community capacity, David Matarrita-Cascante et al. explained the differences and connections among these concepts and further clarified the dominant role of community resilience in disaster response [
12]. Evangelos Ntontis et al. examined how community resilience was used in the UK document on guiding floods to explore how different texts define community resilience [
68]. This study highlighted community resilience’s procedural and dynamic properties and pointed out the main priorities for strengthening community resilience policies, which provides policy suggestions for policymakers [
68]. The meaning and characteristics of resilience are increasingly clarified with the development of systematic community resilience.
Topic two: climate resilience (cluster one and cluster seven).
Climate change is a common challenge facing human society. As societies’ basic spatial-demographic units, communities play a key role in the response to climate change. Climate resilience has also become a vital aspect of community resilience research and practice. For many years, “mitigation” and “adaptation” have been considered as the main strategies to combat climate change [
69]. In the study of dealing with community climate change, academia often takes case studies as a general research method to discuss a community’s climate response. Berkes F. and his collaborators conducted a study on the small community of Sachs Harbour in Canada’s western Arctic from the perspective of socio-ecological resilience. The short-term adaptation mechanisms and long-term adaptation strategies of local residents provide references for other regions to combat climate change. Newly developed co-management institutions can provide opportunities for feedback and connections between different levels, which can improve the learning and self-organization capabilities of the community [
70]. Based on a survey of poor rural areas in South Africa, Anele Mthembu et al. analyzed the biophysical and socio-economic aspects of the region and proposed a bottom-up, proactive, and systematic approach to manage climate-vulnerable areas [
71]. Based on a bibliometric analysis of the literature on mitigation, adaptation, and resilience related to climate change, Rachel Einecker et al. suggest that a high level of research integration should be achieved in this field and that the existing research fragmentation characteristics should be removed [
72]. Climate resilience is a crucial theme of community resilience construction, and research methods mostly use assessment frameworks and indicators as the starting point to explore specific resilience-improvement strategies. DasGupta et al. constructed a five-dimensional framework for assessing the climate-related resilience of coastal administrative blocks of Indian Sundarbans and emphasized the vital function of institutional intervention in effectively building climate resilience in coastal areas [
73]. Climate resilience-building is an important aspect of current community development and a major capability that needs to be strengthened urgently within the international community and cities. UN-Habitat has developed a “planning for climate change toolkit” for urban communities in low- and middle-income countries to better understand, assess and respond to climate change at the local level [
74]. The Asia-Pacific network for global change research has developed a “community resilience tool” for rural communities [
75]. The Intergovernmental Panel on Climate Change (IPCC), established by the United Nations Environment Programme (UNEP) and the World Meteorological Organization (WMO) (Washington, USA), also provides scientific guidance and countermeasures for global climate change risks. The impact of climate change is a key concern at different levels of society. Enhancing climate resilience requires collaboration among different subjects.
Topic three: Social capital mechanism (cluster two).
Social capital is one of the most relevant topics in the process of community resilience development. As the largest cluster in the intellectual base, it is also the second-largest cluster among the research hotspots, fully demonstrating that the role of the social capital mechanism is an important aspect of academia’s focus on improving community resilience. Social capital refers to the ability and willingness of community members to participate in actions aimed at community goals, as well as the process of participation, that is, individuals acting individually or collectively in community organizations, groups, and networks [
76]. Aldrich regarded social capital as the “core engine of recovery” for the community in disasters and believed that survivors who have connections with powerful social networks can obtain necessary information and support and recover faster than those without social network connections [
43]. Previous scholars divided social capital into three types, including bonding social capital (associations among similar members of a group or community); bridging capital (associations among dissimilar members); and linking capital (connections with other members, institutions, or networks that have greater power or authority) [
77]. For individuals affected by disasters, bonding social capital is the most common form of a social network. It is practical to receive assistance from family and friends when disasters come. For example, Chinese families with larger Spring Festival networks were more likely to rebuild their homes in 2008 [
78]. Pfefferbaum, B also called for enhancing community disaster resilience by strengthening social capital and discussed the significance of social capital generated by building team relationships and improving social networks and social connections in enhancing resilience [
79]. Because of the characteristics of social capital, most previous studies have studied the role of social capital in a certain disaster using questionnaires or interviews. In recent years, studies on social capital have focused more on measuring and evaluating social capital through publicly available data. Kyne and Aldrich used publicly available indicators to obtain the social capital index (SoCI), which was applied to counties in the home states of the United States to measure three types of social capital, providing a specific method for the measurement of social capital [
80]. As the central mechanism of community resilience research, the empirical research method of social capital gradually shows important value [
78,
81]. Specifically, studies on the mechanism of social capital increasingly rely on publicly available data rather than questionnaires or interviews.
Topic four: Macro environment and community disaster reduction policies (cluster three and cluster five).
The continuous advancement of globalization accelerated the opening of community boundaries in geographical, socio-cultural, political, and economic fields [
82]. At the community level, these disruptions from globalization pose a huge challenge to dealing with environmental and social change. In the macro environment, some scholars began to pay attention to the impact of the globalization process on community resilience. Wilson et al. believed that capital and economic globalization are important reasons for the blurring of community boundaries [
82]. Community resilience tends to be negatively affected by globalization processes, with community members pursuing vertical integration (global economy) rather than horizontal integration (economic interconnections within and between communities). The key to maximizing resilience is to strike the right “balance” between communities and globalization [
82]. Thus, how national policies guide communities to build resilience has become a major concern for disaster managers and politicians. Geoff utilized the policy corridor theory to analyze the possible impact of national policies on community resilience and explained that building strong community resilience is often an endogenous process and strengthening bonding and bridging social capital is beneficial. However, community-level actors cannot always play a role in resilience-building alone, and a combination of national and grass-roots approaches is the best way to strengthen resilience [
83]. To explore the effectiveness of government mitigation policies on community resilience, Ji and Lee compared disaster loss data in counties receiving the Hazard Mitigation Grant Program (HMGP) in the United States. The results showed that counties that participated in HMGP were less likely to suffer property damage in future disasters [
84].
Topic five: Community resilience evaluation index system (cluster six).
Facing sudden disaster risks, the integrated resilience assessment system has become an important measure to identify the vulnerability factors of the community and improve the adaptability and resilience level of the community. Resilience assessment is the latest development in community resilience. Especially in the last 10 years, there has been a great deal of related research. By reviewing the evaluation criteria of previous literature, community resilience assessment generally includes five dimensions: environment, society, economy, built environment and infrastructure, and system. Community resilience is usually assessed by quantitative methods supported by data or qualitative methods based on public perception and judgment by experts and scholars. Commonly used assessment tools mainly include scorecards, indicators, models, and toolkits. Indicators are more commonly used in research [
17]. Orencio et al. used Delphi technology to invite 20 local decision-makers to explore the vulnerability standards and related factors affecting coastal communities through the AHP method [
85]. The results show that the impact of environmental and natural resource management, sustainable livelihood, social protection, and planning regimes is the most significant, and the obtained comprehensive index has reference value for the resilience-building of local communities [
85]. Based on the development of the Disaster Resilience of place model [
14], Cutter, S.L. constructed the index of community resilience baseline characteristics [
15] and formed the final community resilience baseline index (BRIC) [
86]. The toolkit contains designated scorecards, indicators, and models to measure the mechanism and process of resilience. It is a community resilience assessment method that should be promoted in the future. Schoch-Spana et al. developed the COPEWELL Rubric, a participatory, bottom-up self-assessment tool for community resilience developed in collaboration with community users and national thought leaders to predict the post-disaster operations and resilience of different communities through the joint efforts of different participants [
87]. Pfefferbaum et al. developed a Toolkit for Community Resilience (CRAT), including the CART assessment survey, key informant interviews, data collection framework, and community dialogue conversations, neighborhood infrastructure maps, community ecological maps, and SWOT analysis [
88]. It is a process of community empowerment through information, communication, and assistance to identify problems, solve problems, and plan activities [
88]. It can be concluded that both indicators and other community resilience assessment tools play an important role in improving community resilience. In the future, systematic resilience assessment will become more popular in combining different tools according to the needs of different dimensions.