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Article

Disaster Resilience Differs between Survivors and Victims’ Families: A Semantic Network Analysis †

by
Jae-Eun Lee
1,
Seol-A Kwon
2,*,
Eugene Song
3 and
Sang Il Ryu
4
1
Department of Public Administration, Chungbuk National University, Cheongju 28644, Korea
2
National Crisisonomy Institute, Chungbuk National University, Cheongju 28644, Korea
3
Department of Consumer Science, Chungbuk National University, Cheongju 28644, Korea
4
Department of Fire Administration and Disaster Management, Dong-Eui University, Busan 47340, Korea
*
Author to whom correspondence should be addressed.
†
Convergence of integrated correlation (CONCOR).
Soc. Sci. 2022, 11(3), 117; https://doi.org/10.3390/socsci11030117
Submission received: 30 December 2021 / Revised: 3 March 2022 / Accepted: 4 March 2022 / Published: 9 March 2022
Browse Figures
Versions Notes

Abstract

:
The main purpose of this study is to clarify the difference in disaster resilience between survivors and victims’ families by analyzing the language used in popular literature on disaster cases. The results showed that there were differences in emotions, behaviors, attitudes, role perceptions, etc., between survivors and victims’ families in dealing with a disaster. In particular, survivors remember and think about the situation that occurred at the time of the disaster, which creates resilience to the incident, while victims’ families attempt to establish resilience to the incident by investigating the facts and government countermeasures. While survivors were focused on building their own resilience, victims’ families were more focused on improving government countermeasures to prevent such accidents from recurring. This can be considered as social or national resilience. Based on this comparative analysis, it is necessary to prepare various theoretical foundations for disaster preparedness and resilience, while further elaborating the theory.

1. Introduction

Disasters disrupt habitual and institutionalized patterns of behavior and produce a social shock that leads to social and personal change. Historical examples show that the problems and weaknesses of a given society and the existing social order change after a disaster, while relevant values and essentials are realized (Solnit 2010). Literary works influence audiences’ reactions: children can increase their understanding of various races through multicultural works (Altieri 1993), while didactic literary works help confirm the value and identity of local communities (White 1998).
Most literary works reflect the social aspects of the times. In disaster-ridden areas, disasters naturally appear in literary works. However, although various studies of literary works have been conducted (Clarke 2005; Demers 1993; Razi 2012), there are few systematic studies of literary works related to disasters (Gardner 2014; Liverman and Sherman 2015; Quarantelli 1980), because, when analyzing literary works, researchers lack multiple perspectives or attempts to observe. From a literary perspective on disasters, no concrete research has been conducted on analyzing disaster preparedness or resilience (Iwata-Weickgenannt 2019; Serrano-Muñoz 2019; Han 2020).
On 16 April 2014, the Sewol ferry, carrying a total of 476 persons from Incheon to Jeju Island, sank in the sea near Jindo, leaving 304 passengers either dead or missing. Given that the majority of victims were high-school students, the bereaved parents experienced tremendous shock and pain (Lee et al. 2017). Moreover, factors that added to the stress, such as the failure to rescue passengers due to poor response, sensational and political media reports, the lack of a search process for missing persons, controversy over the enactment of special laws, and the lifting of the sunken Sewol ferry, hindered the normal mourning process and caused long-lasting psychological difficulties, such as re-experience, anger, depression, and isolation (Lee et al. 2017).
According to a survey on support for victims of the Sewol ferry disaster (2016), 60 out of 145 family members of the victims (41.4%) considered suicide, while 6 attempted suicide. In May 2015, one year after the disaster, a victim’s father in his 50s killed himself (Ilbo 2017). Another study reported that 96 of 131 family members of the victims (73%) severed social relations while 87 (67%) quit their jobs (Park 2015). Although four years have passed since the sinking of the Sewol ferry in 2014, the psychological and social pain experienced by the bereaved has been widely reported (Lee et al. 2018a; Woo et al. 2015; Yang et al. 2015).
The present study goes beyond general discussions on the organization (Bajek et al. 2008; Buckland and Rahman 1999; Kirschenbaum 2019), disaster management systems (Abrahams 2001; Alazawi et al. 2011; Careem et al. 2006), and disaster management techniques (Fajardo and Oppous 2010; Jha et al. 2008; Van Oosterom et al. 2006) of disaster research and instead asks, “How much can the experience of an indirect crisis situation through literary works help in a crisis?”.
Literary works influence recipients, provoking various reactions. Altieri (1993) claimed that multicultural works can improve children’s understanding of various races, while White (1998) asserted that didactic literary works help confirm the value and identity of the community.
In other words, no concrete research has been conducted that centers on human nature in disasters from a literary perspective. Therefore, a new approach is necessary to find, analyze, and theorize the abilities of systems and organizations to flexibly respond to crises.
We have entered an era in which everyday life is a disaster due to severe climate change and the economic crisis (depression) that has been accelerating since 2008. While disasters are ever-present, there is little discussion in popular culture about overcoming them. The main objective of this study is to reveal the development direction of national disaster management in the modern age by promoting pro-social behaviors in society through an analysis of disaster literature.
The main purpose of this study is to clarify the difference in disaster resilience between survivors and victims’ families by analyzing the language in popular literature on disaster cases. Through this analysis, this study aims to uncover the development direction of disaster management in the modern state.

2. Theoretical Background

2.1. Survivors’ Resilience

Many disaster survivors suffer long-lasting mental health disorders. According to Rodriguez and Kohn (2008), most disaster survivors have mild or strong mental illness, but only a few receive medical treatment. For most disaster survivors, there is a large psychological impact, and the memories of those affected by the disaster persist for a long time (Joseph et al. 1992), particularly for younger survivors.
According to a long-term follow-up study by Green et al. (1994) on children who survived a disaster, post-traumatic stress disorder gradually decreased over the 17 years after the disaster. However, thoughts of suicide and abnormal behaviors, such as self-destruction, were also revealed.
Morgan et al. (2003) found that life-threatening disaster experiences in childhood remained as trauma for as long as 33 years and had a long-term effect on disaster resilience. According to Gleser et al. (1978), in disaster survivors psychological stress and thoughts regarding toward those who did not survive the disaster often lead to a feeling of self-rescue.
Generally, long-term follow-up studies on overcoming PTSD are mainstream in disaster survivor resilience studies (Fernandez et al. 2017; Hamblen et al. 2017; Lowe et al. 2018; North et al. 2020; Shang et al. 2019). There is a deep connection between disaster survivor resilience and mental health, with differences based on age group (children, adolescents, or adults), but there are also commonalities in long-term mental health and quality of life effects. Therefore, mental health treatment services are a major factor in improving disaster survivors’ resilience, with rehabilitation a vital factor in promoting resilience, and the social support system and community experts’ support also helpful factors (Laksmita et al. 2020).

2.2. Resilience of the Victim’s Family

The family members closest to the victims of a disaster are affected for various reasons, from witnessing the disaster to losing family members. They are harmed in the short or long term, both economically and mentally. However, studies on the necessity of countermeasures for families of disaster victims are insufficient (Dorn et al. 2006).
Kristensen et al. (2010), Lenferink et al. (2017), Boelen et al. (2008), and Huh et al. (2017) found that survivors experience “complex grief” after a disaster, meaning that the loss of a family member is combined with economic loss, unemployment, employment for a living, and a demand for social support to solve the problem.
Davis (2013) has called for a study on negligence, responsibility, and injustice in the problems facing many casualties and survivors of disasters. Bereaved families demand material measures and an apology for the damage caused by the government to overcome the conflict and mental and economic damage that occur through sudden bereavement (Davis and Scraton 1999).
Cao et al. (2013) found a prevalence of 59.5% in family dysfunction among families bereaved by a disaster, including economic difficulties due to old age, divorce or widowhood, direct exposure to the death of children, not having children after a disaster, and creating a poorer family economy.
Despite knowledge of adequate psychosocial support for those facing death, loss, and severe stress in the context of major disasters, it is important to understand what those affected expect from government officials and public leaders. In Jong and Dückers’ (2019) review of studies on the role of government in helping disaster survivors, they found that survivors expect the government to help them recover from disasters in a fair, compassionate, equal, and reliable way. They expect support with practical needs related to the disaster, and assume that the government will coordinate network partners and break bureaucratic barriers.

3. Materials and Methods

3.1. Materials

In this study, we analyzed two literary works: an essay by the families of disaster victims called The Day Knocked on Our Window (Sewol Ferry Disaster Writers Records 2019), which is a record of families of those on the Sewol ferry; and Spring Will Come Again (Sewol Ferry Disaster Writers Records 2016), a record of the survivors of the disaster (Sewol ferry survival student: 16 April 2014) (Sewol Ferry Disaster Writers Records 2016, 2019).
Since disaster resilience tracks change after a disaster, The Day Knocking on Our Window (Sewol Ferry Disaster Writers Records 2019) is important for giving voice to the victims’ families five years after the event, while Spring Will Come Again (Sewol Ferry Disaster Writers Records 2016) gives voice to survivors two years after the event. These works were selected because they directly targeted survivors and victims’ families (Sewol Ferry Disaster Writers Records 2016, 2019).
We selected these two works for the following reasons. First, it is the first essay written for survivors and their families after a social disaster in Korean society (Sewol Ferry Disaster Writers Records 2016, 2019). Second, the essay is composed based on the interview format of survivors and victims’ families and can be used for language network analysis or interview analysis (Kalocsányiová and Shatnawi 2021; Uekusa 2019; Yari et al. 2019). Third, the Sewol ferry disaster is an unprecedented accident that has caused national trauma for a long time in Korean society (Lee et al. 2018b; Kang 2021; Chung et al. 2021; Lee and Khang 2020). Therefore, it can be a basic data that helps to find the resilience of local communities and countries.

3.2. Method

The text-mining technique’s simple keyword frequency analysis is useful for analyzing differences between two texts and for identifying the author’s intention, particularly in literary works (Amado et al. 2018; Choi et al. 2021; Sapach 2020). R was used for text mining, while NodeXL and UCINET64 were used for semantic network analysis. First, from the text collected using R, an open-source statistics program, we (1) removed special characters, (2) cut the text into word units, (3) divided each word into words and endings, and (4) extracted only words (nouns) from them. The data were purified in the following order:
The frequency of occurrence words was analyzed, and the weights of the occurrence words were analyzed in a table. Additionally, to analyze the connectivity between words, bigrams were extracted using R, and the number and centrality of the connecting lines were analyzed using NodeXL. A language network chart was created using NodeXL. A convergence of integrated correlation (CONCOR) analysis was conducted to form clusters by determining the similarity of keywords using the UCINET64 program.

3.3. Analysis

The indices used to compare the differences between network structures derived from language network analysis are the number of links (degree) and centrality, which represent the local characteristics of individual nodes (Jang and Choi 2012). Centrality is an index that evaluates the degree of closeness of each node to the center and is classified into closeness centrality, betweenness centrality, and eigenvector centrality (Hur 2010; Son 2002).
First, closeness centrality indicates how close one node is to another, with the distance between two nodes as the core concept. A high closeness centrality means that the word can be easily linked with another word (Son 2002). Betweenness centrality is a numerical value of the mediating role of a node. A word with high betweenness centrality influences the relationship between other words and plays the role of linking (mediating) words within the network (Lee and Hong 2016). Eigenvector centrality is an index for searching for central words in the overall structure of a network (Bonacich 1987). It considers not only the number of linked nodes but also their importance (Han et al. 2015). In this study, we identified the centrality of a word in the network by using eigenvector centrality according to Doerfel and Connaughton (2009).
Furthermore, the CONCOR, a language network analysis technique, is appropriate for identifying the main topic of a text by deriving a cluster formed by similar words (Kang et al. 2018). This analysis method finds the relationship between blocks by conducting a Pearson correlation analysis of matrices between words that appear simultaneously and identifying blocks of similar nodes based on them (Lim and Joung 2019). It analyzes the similarity between nodes by finding nodes at the same position structurally in the linked relationships of nodes (Kang et al. 2018).
CONCOR analysis was conducted to analyze the similar clusters and structures of words with the main meaning by referring to the eigenvector centrality and number of connected nodes. In this analysis, a dendrogram that categorizes input words was generated using a hierarchical cluster analysis method representing the structural equivalence relationship.

4. Discussion

4.1. Keyword Analysis of Literature Works of the Sewol Ferry Disaster

To analyze keywords related to the disaster in two works, 13,685 words were extracted from Spring Will Come Again, while 18,897 words were extracted from The Day Knocked on Our Window. A total of 100 words were extracted according to their frequency of occurrence and organized as shown in Table 1.
Frequently-appearing words are as follows: First, words related to the entities associated with the accident were common. Survivors often mention persons who were with them at the time of the accident, such as friends, people, us, and teachers. Victims’ families often mention persons related to the victims, such as fathers, mothers, children, and parents.
Equally common are expressions regarding the situation. Survivors use expressions associated with the urgent situation at the time, such as time, phone, situation, hospital, and life jacket. Victims’ families use situational expressions such as bereaved, phone, situation, Paengmok Port, Sewol ferry, school, company, gym, and workplace. This indicates that there are differences between survivors and victims’ families regarding situations and places.
Thirdly, there are expressions of emotions. Survivors use many such expressions, including worry, sorry, wrong, anguish, and comfort, while victims’ families express similar but different emotions, such as worry and tears.
Fourth are expressions related to resilience. When examining words related to overcoming and recovering from a disaster, survivors use many words to overcome mental wounds, such as memory, story, help, comfort, and effort, while victims’ families use many policy-related words, such as fact-finding, president, government, and special law (Table 1).
In general, resilience refers to the phenomenon of recovering from a physical or mental shock. Resilience in a disaster situation refers to a state in which the victim returns to the state before the disaster occurred. Here, the words memory and story are related to counseling, which is often used as a technique for overcoming general PTSD syndrome (Jung 2019; Mahn et al. 2021; Tanaka et al. 2020). The words help, comfort, and effort can be related to the words of help and effort to return to daily life in a disaster situation (Tyler and Sadiq 2018; Mosby et al. 2021; Meduri 2021). The words president, government, and special law generally refer to words in terms of prevention and recurrence prevention after a disaster, and resilience in disasters is highly related to prevention (Turudić and Britvić Vetma 2021; Kansra 2019).
To examine words that appeared simultaneously, a language network analysis was conducted, and the number of connection lines, betweenness centrality, closeness centrality, and eigenvector centrality were checked (Table 2 and Table 3). As a result of analyzing the language networks of survivors, the total number of links was 13,705, and the average number of links per word was 6103. Centrality analysis revealed that the averages of betweenness centrality, closeness centrality, and eigenvector centrality were 5046.70, 0.0000728, and 0.000257, respectively. When examining the eigenvector centrality in the literature of victims’ families, we was the highest, followed by thought, child(ren), situation, talk, phone, appearance, day, last, Jindo Island, sorry, worry, sea, company, special law, missing person, fact-finding, and truth (Table 4 and Table 5).
Next, according to the results of the language network analysis of victims’ families, the total number of links was 19,501, while the average number of links per word was 5913. Centrality analysis revealed that the averages of betweenness centrality, closeness centrality, and eigenvector centrality were 7702.082, 0.000048, and 0.000174, respectively. Among the words that appeared in the literature of survivors and victims’ families, the top 100 words with a high weight based on eigenvector centrality were extracted, and the network of extracted words was examined. As a result of analyzing the eigenvector centrality in the literature of survivors, thought had the highest centrality, followed by people, friends, us, then, friend(s), real, parents, younger siblings, time, story, teacher, worry, that day, etc. (Table 4 and Table 5).
First, the centrality of thinking appeared equally high in the literature of survivors and victims’ families because the study data were analyzed as replies or contents describing respondents’ opinions. Thought is a function of counting and judging objects (Korean dictionary) and is generally used to express one’s opinion on a specific object.
In the literature on survivors, friends, brothers, and younger brothers who were victims of the Sewol ferry disaster were connected with words that recalled the time of the incident, such as real, memory, worries, and circumstances. Equally present were words that evoke accompanying persons at the time of the incident, such as friends and teachers, and guardian words such as mom, dad, and parents.
In the literature on victims’ families, later, appearance, real, sound, time, and story were directly linked to the situation at the time. Paengmokhang, photo, last, and image were directly linked to words associated with the victim.
Regarding the difference in words between survivors and victims’ families, survivors used many words related to the situation and accompanying persons at the time of the incident, while appearing to have a negative connection to the situation and content of the incident and the government’s response.

4.2. Classification of Subjects through the Analysis of Similar Word Clusters in Literature on the Sewol Ferry Disaster

As a result of the analysis, a total of four similar word clusters were generated from the literature on survivors and victims’ families, and four themes were derived by synthesizing the words in each cluster (Figure 1 and Figure 2).
As a result of conducting a similar word cluster analysis (CONCOR) on the survivors’ essay, overall themes were derived for the memory of the victim, family, and accident. First, the first language cluster, consisting of elder sister, parents, that time, etc., and the second language cluster, consisting of first, there (Sewol ferry), and elder brother are related to the survivor’s memory of the person he recalled at the time of the accident. In other words, it can be said that it is a word about the memory of the time when the Sewol Ferry sank, and the memories of one’s parents, brothers, and sisters there. However, the first word cluster contains the concept of time, while the second word cluster contains the concept of space. Therefore, the two similar word clusters were named ‘Recall of temporal accident’ and ‘Recall of spatial accident’, respectively, and the upper theme was named ‘Recall of accident’.
As the third language cluster—My friends, Friend, Year, School, Friends, and Teacher—consists of words referring to the victim of the accident at the time, and the fourth language cluster—Time and Plaintiff—refers to the time of the accident, the two similar clusters were named ‘Accident targets’ and ‘Accident time’, respectively, and the upper theme was named ‘Accident situations’.
The fifth language cluster—Victim’s family, Sewol ferry, Person, One—is composed of words referring to the victim’s family and the location of the accident, and the sixth language cluster—People, story, talk, we (formally)—refers to the content of the accident. Thus, the two similar clusters were named ‘Accident location and targets’ and ‘Situation details of the moment’, respectively, and the upper theme was named ‘Accident targets and details’.
The seventh language cluster—something, mom, mind, and dad—is a summary of the thoughts that survivors had at the time of the accident, and it seems that children at the disaster site recalled their thoughts about their parents. The last and eighth language cluster—we (formally), memory, younger brother or sister—are thoughts after the accident, which can be seen as memories at the disaster site and things about the younger brothers who were lost in the disaster situation. These two similar cluster words were named ‘Thoughts at the time of the accident’ and ‘Thoughts after the accident’, and the upper theme was named ‘Accident description’. The second highest theme of the survivor’s essay was named ‘Memory of the accident’.
As a result of conducting a similar word cluster analysis (CONCOR) on the victim’s family essay, the themes of the remaining family, the truth of the accident, finding the truth, and the environment were derived. First, We (informally), There (Sewol ferry), and Husband can be seen as words that include families and places related to an accident. Someone, His, or Her can be seen as words that include indirect neighbors and people related to the accident. The first word cluster contains subjects that are directly related to the accident, and the second word cluster contains subjects that are indirectly related to the accident. Therefore, the two similar word clusters were named ‘People involved in the accident’ and ‘Neighborhood’, respectively, and the upper theme was named the ‘Community related to the accident’.
The third word cluster—Mind, It (Accident), and Ansan—is composed of words that mean areas with high relevance to the accident, and the fourth word cluster—Child, Disaster, Society, Family, Dad, Moving—consists of words related to the surrounding environment associated with the accident. These two similar cluster words were named ‘Regions related to the accident’ and ‘Surrounding environment’, and the upper theme was named ‘Awareness of the surrounding environment’.
The fifth language cluster—Thought, One, That time, Talk, Person, Victim’s family, Really, Once, People, Truth investigation—refers to words related to finding the cause, truth, and responsibility at the time of the accident, and the sixth language cluster—First, Sewol ferry—concerns the place at the time of the accident. These two similar cluster words were named ‘Questioning the truth of the accident’ and ‘Accident location’, and the upper theme was named ‘Willingness to find the cause of the accident’.
The seventh language cluster—We (formally), and Mom—is a language cluster indicating the victim’s family, and the eighth language cluster—Image, Children, Time, Child—is a language cluster indicating the victim and the victim’s family. These two similar cluster words were named ‘Families of accident victims’ and ‘Accident victims’, and the upper theme was named ‘Related entities’. The second highest theme of the victim’s family essay was named ‘Finding the cause of the accident and responsibility’.

4.3. Sub-Conclusions

According to the analysis of the language network results, the major difference between the survivors’ essay and the victims’ family essay is the memory and recollection of the accident. First, according to the survivors’ essay, survivors have memories and recollections focusing on the person at the time of the accident, the circumstances at the time of the accident, and the content of the accident. Second, the victims’ family essay goes deeper into the question of the person at the time of the accident, the family left behind, the cause of the accident, the person responsible for the accident, and the truth about the accident.
Therefore, we believe that in order to strengthen resilience after a disaster, it is necessary to distinguish between the crisis management of the victim of the accident and the victim’s family related to the accident. In the case of the victim of the accident, a way to relieve the trauma of the accident is needed (Massazza et al. 2021; Le Roux and Cobham 2021; Bountress et al. 2020), and in the case of the victim’s family, a policy (Lee et al. 2020; Park and Bae 2022; Atkinson and Curnin 2020) is needed to relieve the injustice caused by sacrifice and help the left behind families and communities to lead normal lives.

5. Conclusions

With the Sewol ferry disaster in 2014, problems related to social disasters and corruption became social issues. Studies have been conducted in various fields on the Sewol ferry disaster and social disasters, but no in-depth analysis through literary works has been conducted (Huh et al. 2017; Chae et al. 2018; Kee et al. 2017).
Disaster-related literary works do not have a unified conclusion, and the themes are diverse. Considering this diversity, we can indirectly experience new perspectives on disasters in human society (Baque 2019; Chovanec 2019), and learn how the damage of disasters affects its victims. Such experiences enable an indirect experience of trauma in a disaster situation, thereby leading to the acquisition of a mindset for disaster prevention (Thornber 2021).
In addition, literary analysis can not only predict the cause and damage scale of disasters, but also examine the emotional aspects (social exclusion, disgust). This can be used to tackle complex questions about various types of violence caused by disasters (Bhattacharya 2020; Uyheng 2020). In particular, literary texts depicting real disasters are the most powerful works that explore the lives of disaster victims. This reveals how individuals and disasters have affected their lives (Potts 2018; Mika 2018).
Through a text analysis of disaster literature, this study summarizes the characteristics and significance of survivors’ and victims’ families’ perceptions. The results showed differences in emotions, behaviors, attitudes, role perceptions, etc., as perceived by survivors and victims’ families in dealing with a disaster.
First, the group and meaning of the similar words of survivors are as follows. The first theme is the feelings and conditions of survivor’ targets. There are two sub-themes: “the person concerned and feelings” and “the subject involved and the situation at the time”. This theme is formed of words about thoughts, older sisters, parents, first, brother, there, real, once, and related subjects, thoughts, and feelings. In particular, it is composed of words about victims composed of friends, school, and teachers, and words related to the time of the victim, such as time.
The third subject is the victim and the content, which is composed of two sub-themes: ‘the place and object’ and ‘the content of the situation at the time’. This topic consists of words related to ‘place and object of damage’, such as the Sewol ferry, people, and survivors, and words such as stories, story, and people as ‘the content of the situation at the time’.
The fourth theme was emotion and resilience at the time, and was composed of two sub-themes: ‘Emotion’ and ‘Resilient Emotion’. It is composed of words containing emotions such as mind and something, and meaningful words to remember the situation at the time related to memory and construct resilience through it.
Next, the similar word clusters and meanings of victims’ families are as follows. The first is a cluster of ‘objects and subjects’, composed of two sub-themes, the related object and the related subject, in which words are formed around husband, who, our related person, and the subject. The second is the subject of ‘damage situations and emotions’, and consists of two sub-themes: ‘damage-related areas and emotions’ and ‘damage situation’. Words are formed for the area where the victims live, such as Ansan, and the change of circumstances according to the damage situation, such as tragedy, the world, and moving.
The third theme is ‘request to the government for recovery of the case’, which includes two sub-themes: ‘feelings and demands of the government’ and ‘place of damage’. This theme is composed of words that refer to a transparent and truthful case resolution, such as surviving family, real, once, truth finding, and words for the Sewol ferry, the same damage place as the first.
The fourth theme is related to the subject and is composed of two sub-themes: ‘victim’s family’ and ‘victim’. It is composed of words that recall related subjects through their mothers, children, and appearance.
In particular, survivors remember and think about the situation at that time and develop resilience to the incident, while victims’ families attempt to establish resilience to the incident by investigating the facts and government countermeasures.
While survivors focused on building their own resilience, victims’ families were focused more on improving government countermeasures to prevent such accidents from recurring. This can be considered as social or national resilience.
In this study, we analyzed two literary works in which survivors and victims’ families participated to explore the meaning of disaster literary works. However, this study is limited in that it analyzed literary works containing the opinions of only some survivors and victims’ families. Future work should elaborate the results of this study by preparing various theoretical foundations to build disaster preparedness and resilience by analyzing various literary works related to disasters, including essays.

Author Contributions

Conceptualization, S.-A.K., J.-E.L., E.S. and S.I.R.; methodology, S.-A.K. and S.I.R. software, E.S.; validation, J.-E.L. and S.-A.K.; formal analysis, S.-A.K.; investigation, E.S.; resources, S.-A.K.; data curation, S.-A.K. and J.-E.L.; writing—original draft preparation, S.-A.K., S.I.R. and E.S.; writing—review and editing, S.-A.K. and J.-E.L.; visualization, S.-A.K.; supervision, J.-E.L. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2020S1A5B8103910).

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Acknowledgments

We express our gratitude to Changbi for allowing us to analyze the works The Day Knocked on Our Window and Spring Will Come Again.

Conflicts of Interest

The authors declare no conflict of interest.

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Socsci 11 00117 g001 550
Figure 1. Similar word clusters and meanings of survivors.
Figure 1. Similar word clusters and meanings of survivors.
Socsci 11 00117 g001
Socsci 11 00117 g002 550
Figure 2. Similar word clusters and the meanings of victims’ families.
Figure 2. Similar word clusters and the meanings of victims’ families.
Socsci 11 00117 g002
Table
Table 1. Top 100 words in frequency.
Table 1. Top 100 words in frequency.
RankingSurvivorVictim’s Family
KeywordFrequencyPercentageKeywordFrequencyPercentage
1 Friend4213.076361Dad4352.301953
2 Thought4052.959445We (informally)4312.280785
3 Person2852.082572Mom3561.883897
4 We (formally)1821.329923Thought3501.852146
5 That time1711.249543Person3361.77806
6 School1631.191085Children2651.402339
7 Mom1621.183778That time1630.862571
8 Parents1401.023018Friend1580.836112
9 Elder brother1320.96456Parents1540.814944
10 We (informally)1220.891487Mind1330.703815
11 People1120.818414Talk1330.703815
12 Mind1030.752649Family1250.661481
13 Elder sister960.701498Story1200.635021
14 Really960.701498Victim’s family1130.597979
15 Younger brother or sister930.679576His or her1120.592687
16 One900.657654People1000.529185
17 Dad860.628425Phone980.518601
18 Teacher820.599196Situation890.470974
19 Something810.591889Time870.460391
20 Talk810.591889There860.455099
21 Victim’s family760.555353Sewol ferry840.444515
22 Story720.526123School810.428639
23 Brother and sister720.526123Image800.423348
24 Sewol ferry710.518816Son800.423348
25 Time670.489587Paengmokhang790.418056
26 Plaintiff660.48228Someone780.412764
27 There650.474973Child760.40218
28 Adult610.445744First690.365137
29 Memory600.438436Younger brother or sister680.359845
30 Year580.423822Picture680.359845
31 First570.416514Because of670.354554
32 Once550.4019Degree660.349262
33 Because of520.379978World620.328094
34 Phone510.372671Jindo620.328094
35 Family500.365364It610.322803
36 It500.365364Worry600.317511
37 Degree500.365364That600.317511
38 Situation470.343442That day570.301635
39 Someone460.336134Later560.296343
40 His or her460.336134Suhyeon550.291051
41 Hospital450.328827Yeong-i550.291051
42 Worry430.314213Sorry540.28576
43 Mom and dad410.299598Said to be530.280468
44 Incident390.284984Truly520.275176
45 High school380.277676Year520.275176
46 Sorry380.277676Rescue510.269884
47 Understanding380.277676Tear510.269884
48 Mistake370.270369Truth investigation510.269884
49 One person370.270369Once510.269884
50 Later360.263062Confirm510.269884
51 Moment350.255754During490.2593
52 After350.255754Start480.254009
53 Student340.248447Memory470.248717
54 That330.24114Chaewon460.243425
55 Sound330.24114President440.232841
56 Complete330.24114Missing person440.232841
57 That day320.233833Ansan440.232841
58 Image320.233833Study430.227549
59 Injury320.233833Sound430.227549
60 Father320.233833Company430.227549
61 Emotion310.226525Soyeon420.222258
62 Speak310.226525Face420.222258
63 Picture300.219218Teacher410.216966
64 Study290.211911School trip410.216966
65 Middle school290.211911Name410.216966
66 Interest280.204604Government410.216966
67 Fact280.204604Broadcast390.206382
68 Face280.204604Special act390.206382
69 Graduation280.204604Last time380.20109
70 Preparation280.204604Sea370.195798
71 Jihyeon280.204604Speak360.190506
72 Classroom270.197296Dead body350.185215
73 Feeling270.197296Heart340.179923
74 University270.197296Beggar340.179923
75 Name270.197296Next340.179923
76 Cellphone270.197296Contact340.179923
77 Help260.189989Gym340.179923
78 Related250.182682Signature330.174631
79 Life jacket250.182682Sehui330.174631
80 Itself250.182682Moment330.174631
81 News240.175374Cellphone330.174631
82 It was240.175374Fact320.169339
83 Past240.175374Survivor320.169339
84 Last time230.168067Incident310.164047
85 School trip230.168067Condition310.164047
86 Realize230.168067Morning310.164047
87 Place230.168067We (formally)310.164047
88 Floor220.16076Seunghui300.158755
89 Comfort220.16076Soul300.158755
90 Jindo220.16076Text290.153464
91 Activity220.16076Something290.153464
92 Effort210.153453Hoseong290.153464
93 Doeon210.153453Pray280.148172
94 Head210.153453Evening280.148172
95 Nerve210.153453The public270.14288
96 Any210.153453List270.14288
97 Ong-i210.153453Problem270.14288
98 Strange210.153453Funeral270.14288
99 Funeral ceremony210.153453Workplace270.14288
100 Concern200.146145Day270.14288
Table
Table 2. Indices for the analysis results of the language network of survivors.
Table 2. Indices for the analysis results of the language network of survivors.
ItemsFrequencyItemsAverage
Total number of words 13,685Betweenness centrality5046.70
Total number of links 13,705Closeness centrality0.0000728
Number of average links per word 6.103Eigenvector centrality0.000257
Table
Table 3. Indices for the analysis results of the language network of victims’ families.
Table 3. Indices for the analysis results of the language network of victims’ families.
ItemsFrequencyItemsAverage
Total number of words 18,897Betweenness centrality7702.082
Total number of links 19,501Closeness centrality0.000048
Number of average links per word 5.913Eigenvector centrality0.000174
Table
Table 4. Eigenvector Centrality Survivor Top 100 Words.
Table 4. Eigenvector Centrality Survivor Top 100 Words.
RankingKeywordNumber of LinksBetweenness CentralityCloseness
Centrality		Eigenvector
Centrality		RankingKeywordNumber of LinksBetweenness CentralityCloseness
Centrality		Eigenvector
Centrality
1Thought4001,104,645.5150.0001180.0106351Family5159,914.5640.0000960.00222
2People3781,029,859.3900.0001160.0095052Incident6881,618.5080.0000940.00219
3Friend232537,157.4870.0001110.0073553Brothers and sisters5249,138.9190.0000940.00218
4Us238567,193.3200.0001120.0072054Phone4765,816.6830.0000950.00218
5The236527,976.6560.0001100.0069755Complete6088,218.5820.0000950.00218
6School217445,120.4380.0001090.0067356Feeling4231,236.7040.0000950.00217
7Mom207407,762.6390.0001090.0065257Face4770,370.5380.0000950.00217
8Friends170295,378.3400.0001070.0061158That day5254,800.0860.0000950.00214
9We191380,618.6440.0001070.0056659Name4653,341.1940.0000950.00210
10Elder brother146242,018.5700.0001060.0054060Classroom4528,928.0540.0000930.00209
11Mind154287,488.2350.0001060.0053361Middle school4327,414.1040.0000920.00206
12Real143266,545.8430.0001060.0053162Brother and sister4433,588.2950.0000940.00205
13People163275,642.7840.0001040.0049063Cellphone4751,889.6780.0000940.00203
14One132238,413.1760.0001050.0048664That6364,455.1360.0000940.00198
15Parents128228,709.8040.0001040.0046965Mom and dad6369,187.7710.0000930.00196
16Younger brother134209,673.4590.0001030.0045266Jindo4034,310.2120.0000930.00195
17Friends112155,492.9030.0001030.0044167Activity4237,261.4880.0000930.00194
18Elder sister122202,827.0130.0001030.0043668Study5357,727.7730.0000920.00194
19Something113175,813.5660.0001030.0042969Any4140,820.3550.0000930.00193
20Time103144,265.7650.0001020.0040970Realize4028,270.9250.0000920.00192
21Story103137,562.3980.0001010.0040071Adults4027,097.3390.0000940.00190
22Plaintiff92132,396.1510.0001020.0040072Interest4751,435.3750.0000930.00188
23Sewol ferry115175,225.7700.0001010.0039273Contact3126,361.2160.0000930.00180
24Talk99147,325.8060.0001020.0038874Nerve4149,388.4640.0000930.00178
25Victim’s family100130,260.7300.0001000.0037475Preparation4131,737.7700.0000920.00178
26Teacher87113,470.2890.0001000.0034676Last time4129,761.7080.0000920.00178
27First8996,653.5050.0000990.0033677Strange3951,623.3480.0000920.00177
28Year81116,373.2440.0000990.0033678Condition3735,796.0860.0000940.00177
29Because of90118,107.3480.0001000.0033479It was4739,822.0180.0000910.00176
30Memory79106,399.4890.0001000.0033380Injury4435,469.8310.0000930.00174
31Once89109,131.6820.0000990.0033081School trip3836,296.3100.0000910.00172
32Dad100129,303.1230.0000990.0032982Picture4746,250.3100.0000920.00170
33There111201,575.2480.0000990.0032683Life2627,576.8060.0000930.00167
34Degree88127,759.5200.0000990.0031484Fact4651,256.0050.0000920.00166
35After5968,941.1600.0000990.0030185Adult3946,614.6600.0000930.00165
36His or her7191,482.9590.0000980.0028886Graduation ceremony3123,533.8860.0000920.00164
37Hospital74107,261.1210.0000960.0027887Past4235,472.1990.0000910.00164
38Situation81132,003.2070.0000970.0027388News4343,015.0770.0000910.00161
39High school6057,025.4260.0000960.0026489Training institute2914,602.3090.0000910.00161
40Someone6267,257.6730.0000960.0025890Happiness2710,947.0920.0000920.00161
41Moment5659,901.6550.0000970.0025791Place3839,710.8880.0000910.00159
42Later6079,094.2600.0000970.0025592Early3238,763.0660.0000930.00159
43It88128,527.5540.0000950.0025193Thinking3018,682.4760.0000910.00157
44Image5666,300.4030.0000960.0024494Expression3529,366.6070.0000910.00157
45Speak5560,649.6650.0000950.0023995Student3240,437.7440.0000900.00156
46One person4949,525.0130.0000960.0023696Ansan3419,017.3430.0000910.00155
47Sound5167,202.1840.0000960.0023197Just3228,157.7220.0000910.00154
48Worry5167,565.4240.0000950.0022798Emotion4740,643.1650.0000890.00154
49Parents themselves5571,971.1150.0000950.0022699Relationship2924,522.7830.0000930.00154
50Itself4751,451.3050.0000950.00222100Memorial altar249115.5880.0000910.00149
Table
Table 5. Eigenvector centrality of victims’ family top 100 words.
Table 5. Eigenvector centrality of victims’ family top 100 words.
RankingKeywordNumber of LinksBetweenness CentralityCloseness CentralityEigenvector CentralityRankingKeywordNumber of LinksBetweenness CentralityCloseness CentralityEigenvector Centrality
1We (informally)5212,400,719.9440.000080.00951Changhyeon88183,523.9250.000070.002
2Thought3611,327,268.7290.000080.00852School trip6593,905.6950.000060.002
3Dad3701,448,164.0240.000080.00853Younger brother or sister88192,818.7500.000060.002
4Person4331,866,307.5380.000080.00754Victim’s family89173,248.1180.000070.002
5Mom3241,163,304.0440.000070.00655Once86175,876.4710.000070.002
6That time251801,638.1160.000070.00656Tear76170,248.6680.000070.002
7Mind198552,417.1070.000070.00557Name68123,609.7020.000060.002
8Kid199594,910.9290.000070.00558Ansan81179,029.6480.000070.002
9Children175571,990.6360.000070.00459During78192,331.2140.000070.002
10One170469,513.8970.000070.00460Chaewon72116,743.0820.000060.002
11His or her171582,865.0860.000070.00461Confirm6081,204.9040.000060.002
12Junwoo177427,407.6270.000070.00462Sorry5469,089.1400.000060.002
13Situation151401,032.4280.000070.00463Moment5581,109.9950.000060.002
14People154429,192.9930.000070.00464Father89193,064.2800.000060.002
15Talk136329,930.4650.000070.00465Year74117,156.0320.000060.002
16Geonwoo145317,728.5390.000070.00466Worry63124,914.9130.000060.002
17Time157449,182.1240.000070.00467Next59103,981.7170.000060.002
18There150473,916.3650.000070.00468Mother77173,680.1360.000060.002
19Story157477,185.2720.000070.00469Families68130,205.2170.000060.002
20Parents137369,294.7880.000070.00470Gym5192,895.4660.000060.002
21Paengmokhang123274,331.1620.000070.00471Sea61139,750.5760.000060.002
22Friend125309,847.5640.000070.00472Soul5791,362.4860.000060.002
23Someone126307,432.0170.000070.00373Company68151,685.1930.000060.002
24First120281,975.9130.000070.00374Heart59109,827.8870.000060.002
25School128266,509.3470.000070.00375Suhyeon82181,889.3640.000060.002
26Phone121256,073.5540.000070.00376Dead body5898,701.1950.000060.002
27Son104203,350.6830.000070.00377President71137,825.6510.000060.002
28Truly87157,956.4640.000070.00378Funeral4766,415.3480.000060.002
29Picture109243,843.9130.000070.00379Memory53104,833.9490.000060.002
30Image102235,379.3100.000070.00380Fact5764,157.3410.000060.002
31It105246,342.6790.000070.00381Hoseong4651,871.5660.000060.002
32Said to be90197,001.1510.000070.00382Study5189,378.6510.000060.002
33Child101232,998.8170.000070.00383Speak62121,806.3520.000060.002
34That103235,481.8740.000070.00384Contact59110,601.7040.000060.002
35Jiseong106284,202.1880.000070.00385Special act63128,530.1080.000060.002
36Degree114303,178.1250.000070.00386Beggar60106,523.2240.000060.002
37That day97187,892.7310.000070.00387Something5475,477.9980.000060.002
38Friends86142,484.1620.000070.00388Government64141,019.5660.000060.002
39Jindo100243,281.1450.000070.00389Missing person5071,540.4470.000060.002
40World96185,850.4220.000070.00390Truth investigation67150,491.9520.000060.002
41Sewol ferry127344,333.8970.000070.00391Victims’ families60127,036.3930.000060.002
42Last time5874,031.6430.000070.00392Seunghui5162,628.4820.000060.002
43Yeong-i85162,308.6020.000070.00393When thinking3147,871.8550.000060.002
44Sound68126,313.8040.000070.00294Alone3759,298.1410.000060.002
45Face66152,377.5820.000070.00295Cellphone5160,209.5230.000060.002
46Start88201,449.7090.000070.00296Text4555,284.7790.000060.002
47Miji90157,766.4630.000070.00297Morning5367,706.5410.000060.001
48Later88201,832.5850.000070.00298Baby4552,655.1550.000060.001
49Because of120307,073.8050.000070.00299Broadcast4877,768.9850.000060.001
50Family90191,116.1220.000070.002100Truth4357,479.3810.000060.001
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Lee, J.-E.; Kwon, S.-A.; Song, E.; Ryu, S.I. Disaster Resilience Differs between Survivors and Victims’ Families: A Semantic Network Analysis. Soc. Sci. 2022, 11, 117. https://doi.org/10.3390/socsci11030117

AMA Style

Lee J-E, Kwon S-A, Song E, Ryu SI. Disaster Resilience Differs between Survivors and Victims’ Families: A Semantic Network Analysis. Social Sciences. 2022; 11(3):117. https://doi.org/10.3390/socsci11030117

Chicago/Turabian Style

Lee, Jae-Eun, Seol-A Kwon, Eugene Song, and Sang Il Ryu. 2022. "Disaster Resilience Differs between Survivors and Victims’ Families: A Semantic Network Analysis" Social Sciences 11, no. 3: 117. https://doi.org/10.3390/socsci11030117

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