Abstract
This article argues that both direct and indirect social networks between volunteers had become social capital for them to help the Syrian refugees in Slemani City, Kurdistan region, Iraq. This argument is based on a recent study that had applied a combination of social network, structural hole and social capital theories, and social network analysis methodology, namely ego network analysis. The research objectives were to uncover the nature of social networks that had generated social capital through analyzing the structure of social networks between the volunteers (i.e., who is linked to who) and the type of their social networks. Data were collected through semi structured interviews and network-based survey from a purposive sampling of 20 volunteers in a non-governmental organization (NGO) selected for the study. Findings revealed the structure of social networks as established by a type of social network known as friendship ties between the volunteers. The volunteers’ social networks had also generated social capital for them because the networks had added value. Hence, the networks provided the volunteers benefits, namely task, informational, and social support benefits. Specifically, the volunteers obtained task benefits by assisting one another in building and renovating, maintaining good hygiene and tool services in the refugees’ shelters and distributing non-food items. Informational benefits were in terms of cooperating and advice giving and getting information to assess the refugees’ family situations and conduct seminars and campaigns for the refugees. The volunteers also received social support benefits through social gatherings. These findings imply the need for the Kurdistan government and NGOs to emphasize social networks and social capital to motivate volunteers.
The current refugee phenomenon is one of the most difficult humanitarian challenges and tragedies in refugees’ history (Aziz et al., 2014; UNHCR, 2014) According to the statistics of the United Nations High Commissioner for Refugees, at the end of 2019, 79.5 million people around the world were forced to flee their homes because of conflict and persecution, 26 million of them were refugees who mainly came from the Middle East including Syria, and left their country against their will (UNHCR, 2020a).
A refugee is a person who has fled his/her country due to experiencing a bad situation within the country, such as war and violence, to reach safety (UNHCR, 2020c). In Syria, residents have left their country because of war (Reid, 2020). As of 23 September 2020, (5,565,954) Syrian refugees have registered in the neighboring countries, including Iraq, which hosts (243,011) refugees and from that number, Slemani has welcomed 31,099 refugees as of 31 July 2020 (UNHCR, 2020b). Slemani is a city that in the Kurdistan region of Iraq, located on the border with Iran, in the northern of Iraq (NCCI, 2015). The last census of Slemani’s population was conducted in 2016 and recorded 2,110,000 million people (Slemani Governor, 2018). The majority ethnic group is Kurdish, and the main religion practiced is Islam, although the city hosts other ethnic groups and religions (NCCI, 2015). Iraq is not a part of the convention on refugees which was signed by 149 nations to define and determine refugees’ issuse (UNHCR, 1951), but, as cited by Sadek (2013), it allows refugees to obtain work, for example, similar to Iraqis according to Iraq’s Act No 51 of 1971 (Iraq: Act No. 51 of 1971, The Political Refugee Act, 2020). In addition, the 21-2010 law from the Ministry of Migration and Displacement helps and supports refugees by providing services inside of Iraq (Sadek, 2013). Besides the above positive factors, refugees have many great supporters who supply them with essential needs both inside and outside of the camps, such as the government of the Kurdistan Region in close collaboration with international agencies and non-governmental organizations (IMS, 2014). But, there are still some unsolved economic, health, educational, and social difficulties facing Syrian refugees (Hamada, 2016).
Syrian refugees have a right to work as citizens in Kurdistan, but there are many unemployed refugees and a lack of livelihood options (Ground Truth Solutions, 2017; Hamada, 2016). These economic challenges cause refugees to face other difficult situations, namely educational, health, and social problems as described below.
Refugee families enroll their children in school at a low rate and encourage their children to seek a job instead of thinking about studying as using the Sorani Kurdish dialect instead of Arabic is another problem well (El-Ghali et al., 2017).
Regarding health challenges, refugees have free access to health services in the public hospitals in the city, but when they have operations or when they have to buy medicines outside the hospitals and visit clinics, they face hindrances because they have a lack of income (Hamada, 2016). Concerning the social situation, refugees generally do not have negative relationships with the host citizens because the citizens and refugees share a similar culture, language, and ethnicity. Moreover, when the UNHCR provides cash assistance (UNDP & UNHCR, 2017), the difficulties have appeared in the relationships among some of the refugee families because refugees do not get assistance equally (Hamada, 2016).
The non-governmental organizations conduct activities of public interest in various fields, such as charitable and health concerns, which constitute a vital a rea of volunteering activities (Manswri, 2015). Volunteering to help other people, such as resettling refugees, provides social capital in the form of benefits such as adjustment within the new environment (ICMC Europ, 2015). Volunteers would typically establish social relationships with other volunteers in carrying out their volunteering work, more so if their volunteering work is constantly challenging with many issues and problems. Hence, they normally do not operate independently of other people. This situation is evident even among the volunteers who help the Syrian refugees in an NGO located in a refugee camp in Slemani City. Despite that, studies on Syrian refugees are still negligable or lacking till today, more so for studies on volunteering for the refugees.
Moreover, while previous literature on volunteering for refugees of other nationalities acknowledged the presence of social relationships or social relations in volunteering work and acknowledging social relations as an important feature of volunteering work, they do not study the structure of social relations systematically and how social relations, specifically social networks between particular individuals (i.e., volunteers) that can become social capital (generate benefits) for the volunteers to play a key role in facilitating and coordinating effectively the challenging volunteering work for the refugees. In fact, a systematic study on the structure of social networks, that is, who is linked to whom, can portray clearly on how exactly the interlinked volunteers obtain social capital from their networks and how the networks and capital enabled them to overcome some volunteering challenges and conduct effective volunteering work together with other volunteers.
Furthermore, despite some studies on social networks and volunteering, there is still a general lack of study on social networks and social capital for volunteering, especially direct and indirect social networks that can provide benefits (otherwise known as social capital) to social actors, that is, volunteers, involved in the volunteering work. Social networks are a series of social relations (or social ties) established between at least two persons to conduct an activity together and gain benefits together (Harrington, 2003; Wasserman & Faust, 1994). As for social capital, it is a form of non-monetary and non-economic capital that gives added value to social actors (Bourdieu, 1986). This added value is also considered as “benefits.” Social capital is often contrasted with human capital and physical capital. There are three typical types of social capital and they are social networks, trust and norms (Coleman, 1994; Putnam, 1995a). More succintly, social networks become a social capital when they provide added values and therefore generate benefits to the actors who are involved in the networks. In other words, social capital is benefits derived from social networks; those who are linked to one another through social networks will all get capital or benefits from their linkages. Social capital is an outcome of effort to establish the social networks.
There are also limited studies on using social network analysis as a methodological tool to analyze social networks or basically social relations empirically. Social network analysis is a less standard but useful survey method to collect quantitative data on social relationships (i.e., overall social networks structure and also ego network structure) and analyze them as compared to common quantitative methods of data collection and data analysis (Edwards, 2010). Social network analysis is capable of analyzing quantitatively in a systematic way the structure of social networks to see who is linked to who in the conduct of their activities, the reasons for their linkages or ties, and outcomes of the linkages (Bolíbar, 2015; Edwards, 2010). Hence, the social capital as an outcome derived from the social networks can be ascertained clearly and convincingly. Social networks analysis can also study social network data qualitatively to further support the quantitive analysis. In short, the research gaps that the authors of this article wish to fill through a recent study on the structure of social networks (i.e., ego networks) and social capital for volunteering for Syrian refugees is seen at the theoretical, methodological, and empirical levels. The following section on literature review will explain further the gaps.
The research gaps outlined have prompted the authors of this article to conduct the social network analysis study of volunteering for Syrian refugees to argue for the importance of social networks as a theoretical, methodological, and empirical tool to generate social capital for the volunteers. Volunteering for Syrian refugees is a good case for testing the theoretical-empirical relationships between social networks and social capital because the authors were able to further prove and substantiate an existing common argument in some literature on the importance of social networks for volunteering for refuges by conducting a sociological study that applied Coleman’s and Burt’s theories and social network analysis methodology. As such, the authors were also able to contribute further new empirical knowledge on the role and importance of social networks as social capital for volunteering for refugees, particularly Syrian refugees compared to other studies. Specifically, the authors were able to show clearly the social networks structure (ego-based), that is, who was linked or networked to who (or which volunteer was linked to which other volunteers) in doing volunteering work, and also what volunteering activities that they conducted together. Finally, specific kinds of social capital (benefits) that each volunteer had received from their linkages or social networks (i.e., which volunteers received what social capital or benefits from which other volunteers that they networked with during volunteering) could be confirmed as well as how those capital had helped them in their volunteering work for the refugees. Therefore, the Syrian refugee case is also a good case to study because it has not been studied before sociologically using social network analysis theory and methodology. The combined application of both social network and social capital theories has also not been done before by other studies. Hence, the Syrian case study is novel while being sociologically based and empirically enlightening at the same time.
The aim of the authors’ study is to substantiate an argument that direct and indirect social networks do contribute to bringing benefits in the form of social capital to the volunteers and that capital enabled them to carry out their volunteering which can be challenging and testing at times. In particular, how did the networks become social capital to the volunteers and what are the kinds of social capital that have been created from the networks are queried through two main research questions. The questions that have guided the analysis are as the following: -
RQ1: How did social networks become social capital that enabled the volunteers to carry out their volunteering activities for the Syrian refugees?
RQ2: What are the the social capital (i.e., benefits) that the volunteers received from their social networks?
The first research question has been answered through a structural analysis of the social network structure while the second research question has been answered through the analysis of kinds of benefits, that is, social capital received by the volunteers. The structural analysis uncovered the nature of social networks that had generated social capital for the volunteers, that is, who is linked to who directly or indirectly, the type of their social networks between the volunteers (e.g., friendship ties) and how those networks had generated capital or benefits for the volunteers. This article presents and discusses some findings from the study. The following section presents the literature review of volunteering and social networks in different social contexts.
Literature Review
This literature review serves to demonstrate some research gaps evident at the theoretical, methodological, and empirical levels concerning the study of volunteering for refugees. The gaps are then filled by the authors through a recent study. Filling the gaps confirms the contribution of the authors’ study on social networks and social capital for volunteering for refugees, namely Syrian refugees, from a sociological perspective.
From a sociological perspective, volunteering, as cited by Wilson and Son (2018), is related to social networks. There are several studies that have investigated social networks and volunteering (Abbasi et al., 2012; Brown & Ferris, 2007; Dávila, 2018; Dury et al., 2015; Einolf & Chambré, 2011; Herzog & Song, 2018; Principi et al., 2016; Wilson & Musick, 1997; Wilson & Son, 2018). Wilson and Musick (1997) examined direct social networks as a significant resource—social capital resource—to support volunteering, however, they did not study whether volunteering can also be done through indirect social ties (Burt, 1992). Applying the integrated theory of volunteering as one sociological approach to the topic, they found that direct networks such as conversations and meet with friends and volunteering are significantly related to one another. To do volunteer work, people need to have ties with friends because these ties “embed” some resources such as information that can help support the volunteering actions (Wilson & Musick, 1997).
There are causal relations between direct connections such as neighborhood relationships and volunteering. Based on the results of researche folloing quantitative approaches, people who frequently had contacts in the neighborhood such as visiting and sharing information and depended on their family ties to volunteer were more involved in volunteering (Henriksen et al., 2008; Wilson & Son, 2018). Moreover, Dávila (2018) examined friendships and acquaintances (direct connections) in relation to volunteer work among older Spanish volunteers. They found that the volunteers’ network structure was positively related to volunteering; volunteers were encouraged through their connections with friends and acquaintances who also volunteered. However, this study questionably did not frame the social theory, although it did powerfully recognize a relation between different types of social networks and volunteering as a social activity.
Likewise, in a quantitative study among older adults in Belgium examining a hybrid theory of volunteering, Dury et al. (2015) found that frequent contact with friends (in terms of visiting and calling friends frequently—direct connections) was the only positive significant social factor that encouraged older adults to volunteer. More specifically, in another study in 2020, Dury et al. applied the sociological aspect of hybrid theory adapted from Einolf and Chambré (2011). In their recent study, the researchers used the social connectedness theory of volunteering to explain how formal and informal ties affect the choice to become a volunteer. In contrast to earlier studies, they applied a mixed-method research design and collected data from older Belgian adults regarding their contact with their families and friends, as well as contacts within organizations. According to their findings, direct formal networks helped older adults decide to volunteer in later life (Dury et al., 2020). Although the researchers used a different theory of volunteering that is not based on social network theory and method, the findings still suggest the same explanation of the dependence of volunteering on supporting resources, as volunteering is encouraged through social capital resources (Einolf & Chambré, 2011). The study did not focus on achieving a structural understanding and analysis of social networks, especially with the issue of indirect ties. Also, the above-mentioned studies were done in different contexts among people who were mostly in the later stages of life. None of the studies were done in Slemani City. The different contexts may, of course, lead to different outcomes.
In contrast to the standard studies mentioned above, in a network study design, Abbasi et al. (2012) examined the structure of social networks. They conducted a helpful study on co-authorship networks, not with volunteering, but with another variable of interest, namely research performance. In an ego-centric study using structural hole theory and the social network analysis method to analyze data, the aim of Abbasi et al. (2012) was to find correlations between the structure of collaboration networks and research performance;. The results of their study showed that scientists who had strong ties with other authors who were not directly connected with each other were able to achieve a better performance. Also, the scientists who were linked only as co-authors in a group where the other co-authors were not socially connected had better performance (Abbasi et al., 2012).
Those studies mainly focused on examining the association between social networks and volunteering, but only coming from the common focus on direct as opposed to indirect ties, as well as the outcomes of these ties. The present study conducted by the authors is in the field of sociology, and is able to study the social networks of volunteers, especially those contributing to increasing the sociological understanding of indirect networks as well as direct networks, in order to help volunteers in their activities. It specifically studies the connection between indirect ties and volunteering. The studies examined actors and their volunteering behavior as independent units (grouped network structure as an attribute variable of volunteering), but did not explain how volunteers’ social ties and their social behavior (volunteering) are interdependent units. The authors, thus, conducted a study based on a social network analysis to explain how volunteers’ social ties and their social behavior (volunteering) are interdependent. Also, the previous research applied theories of voluntary actions that generally explained capital resources (social, human, and cultural) related to “volunteering” (Dury et al., 2020; Henriksen et al., 2008; Wilson & Musick, 1997). The theories argued that capital resources could effect volunteering through social networks. However, thus far, it has not yet been studied how the structure of networks as linking people together can be a means of completing actions. Those studies also did not apply social capital theory and structural hole theory (Abbasi et al., 2012) to investigate other issues except volunteering. So far, there has been no clear theoretical foundation addressing the relationship between social networks and volunteering based on a combination of basic social network theory, structural hole theory, and social capital theory.
Another limitation has to do with the research methodology. The reviewed studies followed standard social survey methods (Dury et al., 2020; Wilson & Son, 2018), except for Abbasi et al.’s (2012) research, but they did not apply social network methodology using social network analysis. The study by the authors is quite different from other studies for this reason, as it conducted a network research. It is therefore interested in studying structures and patterns. For this, social network analysis can be a suitable and crucial structural method. The information gap relates to both empirical and practical knowledge. The findings and practical aims of the previous studies were not combined with the volunteering world in a significant way to explain how social networks helped refugees to adjust, and could not offer guidance to authorities based on their findings. They only focused on the narrow action of volunteering itself.
Theoretical Understanding of Social Networks and Social Capital
In the authors’ study, a combination of basic social network theory, structural hole theory, and social capital theory is applied to understand and explain the research problem. Social network theory is a theory as well as a methodology to study social structures systematically at the individual or group levels (Borgatti & Halgin, 2011; Chan, 2017a, 2017b; Scott, 1991). Depending on the theoretical perspective, the relational ties between individuals establish the structure of social network, which in turn affects individual actions (Kirke, 2009). According to social network theory, individual actions are the relational outcome of the individuals’ relationships with one another; such outcomes are otherwise absent should the individuals failed to establish those relationships. Therefore, this theory presents a relational understanding of social phenomena emphasizing people’s networks more than their individual attributes (Wasserman & Faust, 1994; see also Chan, 2017a, 2017b). From this perspective, the central notion is that of social networks (Borgatti & Ofem, 2010).
Social networks consist of two main elements: a set of actors and the connections between them (Crossley et al., 2015). A network is like a chain, where a person connects with some other people or links in the chain, and then those others connect with still others and so on, continuously forming new chains and new links in those chains. The set of actors involved in social networks have been termed “egos” or “nodes” in social network literature, and between them, the connections are formed (Kadushin, 2012; Scott, 1991; Wasserman & Faust, 1994). From the perspective of network theory, ties connect people together that allow and enable them to receive more opportunities in life; people’s social context is considered to be extremely important, as being with other people has been shown to provide multiple benefits as opposed to being by oneself (Borgatti & Ofem, 2010).
Another key idea in social network theory is that social actors are able to establish social networks because they have similarities between themselves, for instance, similarities in socio-demographic characteristics, views, mindsets, behavior, positions, memberships in organizations, and others (Balkundi et al., 2007; Chan, 2017a, 2017b; Chan et al., 2011, 2020; Christakis & Fowler, 2009; Kilduff & Tsai, 2005; Norizan & Chan, 2022; Scott, 1991) . Examples of socio-demographic characteristics are age, religion, gender, level of education, ethnicity, place of birth, place of residence, and others.
As mentioned earlier, social network theory is closely linked to social capital theory. Social networks are one of three types of social capital. The main idea of social capital theory is that social capital is created through social network structures (Coleman, 1988; Field, 2003; Nahapiet & Ghoshal, 1998). In other words, social networks provide benefits; specifically social networks generate added value to the network actors and the value is termed and understood as “capital” which is a particular form of non-monetary capital known as “social capital” (Coleman, 1988; Helliwell & Putnam, 1995; Putnam, 1993, 1995b). In short, the value is considered as “benefits” in terms of “social capital” that the network actors gained from their social networks. The chosen theory for the authors’ study is social capital theory as put forward by Coleman (1994) and also Burt’s (1992) structural hole theory.
Coleman’s theoretical notion coheres with the authors’ research problem; he focuses on network structure, direct ties in particular, and on obtaining benefits at the individual level.
Coleman (1988, 1994) identified “closure” as one of the properties of a social network structure, and argued that this closure is a source of benefits for network members, which he, thus, called “social capital.” For Coleman (1988, 1994), closure means strong or direct connections between or among people, and when networks have closure, it means that everyone is connected with all the others in the network (Burt, 2001; Gargiulo & Benassi, 2000). Coleman (1994) explains that the benefits obtained through direct networks are classified into three main types, namely norms and sanctions, information flow, and obligation and expectation. The authors’ study focused solely on benefits in terms of information flow benefits. This choice was based on the interview data collected during the research. It became clear from the data that volunteers needed other volunteers in order to be guided or given assistance during the volunteerin that is in line with Coleman (1988, 1994) point.
The authors further linked social capital theory by Coleman with a specific social capital theory propagated by Burt called structural hole theory. American sociologist Ronald Stuart Burt is considered to be the leading and most prominent scholar to create a bridge between social networks and social capital through his work on “structural hole theory” (Baron et al., 2000; Koput, 2010). The main idea behind structural hole theory is that a social network’s structure determines the benefits its members receive; this argument differs significantly with Coleman’s argument (see Burt, 1992 on structural hole theory). . Practically, it looks like this: If you connect with only close friends, your resources for getting information are limited, but if you connect with other possible networks, then you have more chances to access different types of information (Esser, 2008). Structural hole theory is developed to describe how certain network structures provide benefitsFor Burt, certain network structures feature indirect ties, which he terms “structural holes”; “holes” mean absent or missing ties between two persons who are connected to others in the network but not each other (Perry et al., 2018).
Burt (2000) believes that there are two kinds of network benefits derived from having indirect ties in a network structure; the benefits are information and control benefits, which then lead people to attain their goals or rewards (Perry et al., 2018). The author’s study analyzed information benefits, in addition to task benefits and social support benefits. The motivation for studying these benefits is based on an interest in what volunteers actually need in order to carry out their volunteering activities, and is not interested in power and influence. Based on the interview data, volunteers needed each other to obtain information; there were no volunteers acting as coordinators to manage all the other volunteers. Mostly, volunteers needed one another to receive benefits.
According to Burt (1992), an information benefit determines who knows about new projects or new jobs, for example, when they can know and who then gets to work on them The access feature of a network means that when a person is connected to others who are not directly connected to each other, then the first person is likely to have a greater opportunity to get more information (with little redundant information) compared to other people by being able to reach more people (more sources of information benefits). In addition, timing, for Burt (2001) means giving a person information earlier than other people; having indirect ties in a person’s network structure allows the person to obtain information earlier. Regarding referrals, being connected with others will allow you to mention “your name at the right time in the right place, so opportunities are presented to you” (Burt, 1992). The study conducted by the authors of this article applied social network theory in combination with social capital theory by Coleman and Burt.
In a similar line of argument with Coleman, Putnam (1993, 1995b) through his study in Italy and America contends that social networks did produce social capital that has a collective feature at the aggregate level. Putnam (1995b) defines social capital as features such as networks that facilitate coordination and cooperation for mutual benefit. He explained that when people in organizations or clubs connect together, mainly through strong ties, and when they interact together and cooperate and assist each other, then the benefits can be enjoyed by all of the members of the clubs or organizations (Putnam, 1993). Thus, the more people connect and offer others cooperation and mutual assistance, they trust each other, then, the more benefits, such as information, are enjoyed by whole population of an organization, city, region, or country (Putnam, 1995b). Overall, a lack of connections—strong social ties—reduced the number of people acting together to pursue shared goals (Putnam, 1995b, 2000).
In short, how social networks produce social capital has been specifically analyzed and empirically discovered is mainly through a combination of Coleman’s theory and Burt’s theory and social network analysis methodology. Putnam’s social capital theory further supported the application of Coleman’s and Burt’s theories. Coleman (1991) argues that social networks create social capital while Burt claims that indirect social ties or networks also do generate social capital. How did the social networks produce social capital for the volunteers is confirmed at the conceptual, theoretical, methodological and empirical levels. Firstly, the authors conceptualized social networks and social capital and then operationalized and measured the networks and capital. Social network theory, social capital theory and Burt’s structural hole theory are the basis of the conceptualization, operationalization and measurement. Putnam’s social capital theory further supports (see Helliwell & Putnam, 1995; Putnam, 1993, 1995b). Secondly, the authors employed social network analysis methodology to conduct a structural analysis of the structure and patterning of direct and indirect social networks between the volunteers, that is, who was linked to who, and who gets what benefits (social capital) from who. The methodology is based on basic social network analysis as well as Burt’s structural holes’ analysis of indirect ties that produce social capital. The following sections will explain the methodology and reveal the findings based on those theories.
Research Methodology
The social network research methodology is based on a combination of qualitative and quantitative approaches. This methodology became the basis of the research design which is a network study design. A network research design is unlike a typical social research design. This design is specially created to conduct social network study and social network analysis (Wasserman & Faust, 1994). This design requires several aspects related to social network study and analysis. The aspects are network actors (who is involved in the networks), the patterns of social networks or social relationships that link the network actors (who is linked to who), basis (reasons) of the networks (why are the networks formed), content of the networks (what are the networks all about), form and structure of the social networks (how does the patterning or linking of the networks look like), and finally effects of the networks upon other actors (what do network actors get out from their networks; Chan, 2015, 2017a, 2017b; Wasserman & Faust, 1994).
Network actors are called “nodes” while the relations between the nodes are known as “ties.” The ties that are linked to create a social network or several social networks. Hence, social network analysis is a particular kind of analysis that studies systematically patterns of social relationships (the ties) between the nodes, who is linked to who. The nodes (actors) can be individuals, groups of individuals, or organizations. In the study, it was systematically traced the patterning of social networks between the nodes (i.e., volunteers) to uncover who were the nodes involved in the networks, the nature (network structure, network types), the basis (or reasons) for the formation of the networks, the content of the networks and the network effects upon other nodes (network actors who were also volunteers); effects in terms of outcome of the networks, that is, benefits or also known as social capital.
Furthermore, social network analysis can focus on a whole network established between several actors (nodes) simultaneously or just single actor networks (otherwise known as ego network). For the authors’ study, it focused on ego networks, that is, single networks of individual volunteers (nodes). Ego network studies the social networks that an individual volunteer (also known as ego) established with other volunteers. However, specifically to the study of ego networks, those other volunteers are not called “ego” but “alter.” When those other volunteers gave help, they were actually giving benefits to the volunteers (egos). That means the volunteers (egos) obtained benefits (social capital) from those people (alters). In this study, the ego network approach is used for a number of reasons related to the aim of the study. The authors studied the social networks of each volunteer, who is accordingly called an ego, and the direct and indirect ties with the alters in the network, who were other volunteers. The study analyzed all the egos’ network structures to identify their ties with other volunteers (alters) and particularly to understand how the egos’ networks generated social capital for them in terms of the benefits they received from those other volunteers (alters). The benefits ultimately helped the egos in their volunteering work. Hence, in this ego-centric network analysis, the network structure of each volunteer (ego) who worked at the NGOs helping Syrian refugees in Slemani is of interest (and not just the entire network structure as a whole). Thus, the main unit of analysis for the study is the volunteers (egos) themselves, who were directly involved in the volunteering.
Population, Sample, and Sampling of the Study
The population of the study is all volunteers who were doing volunteering for Syrian refugees in Slemani City, Kurdistan Region while the sample is selected volunteers. Semi-structured interviews initially identified the population of volunteers in the NGO and consequently identified the sample and determined sampling process of the study. The population of this ego-centric network study included all the volunteers from all 11 NGOs in Slemani City who were involved in volunteering with Syrian refugees there. The study aimed to pinpoint how the social networks of volunteers generated social capital (i.e., benefits) had helped the volunteers to do their work helping Syrian refugees in Slemani city at the NGOs. Hence, the focus is on volunteers who helped Syrian refugees in Slemani City.
The sample of the study included selected volunteers in two NGOs in Slemani City. The two NGOs were from a total of 11 NGOs in the city and were based in a Syrian camp in the city. Hence, the population of volunteers consisted of all volunteers from 11 NGOs. From that population, a total of 20 volunteers from the two NGOs who were directly involved in volunteering for the Syrian refugees were selected through non-probability purposive sampling. Actual names and numbers of egos (volunteers) and their alters (other volunteers) were obtained but their names and their NGOs’ names are concealed for research ethical reasons. The samples volunteered for several particular departments such as wash and shelter department, and hygiene department in the Syrian camp.
The sampling was purposive because the samples were selected based on their volunteering work for the NGOs and willingness to participate in the study, Thus, the 20 volunteers were the units of analysis for this study. Therefore, the study did not aim to synthesize generalized results for all 11 NGOs. Please see Table 1 for the list of volunteers, whose names have been concealed for ethical reasons. They were not involved with other parties such as the UNHCR or the Kurdistan Regional Government (KRG) because the UNHCR was not conducting programs and activities with its own volunteers. As for the KRG, it supervised the administrative aspects and security of the camp only. It was not involved in conducting essential activities for the refugees.
Background of the Study Respondents.
Data Collection
Data collection is based on mixed-method social network analysis, including the ego-centric analysis, that involved combining quantitative and qualitative approaches in order to understand and analyze the structure of social networks. First stage data collection collected data through semi-structured interviews with eight volunteers at the NGOs within the camp (three of them from the hygiene department, volunteers 1, 2, and 5, and three of them from the wash and shelter department, volunteers 4, 7, and 9 in a NGO, two of them from another NGO, volunteer 2 and volunteer 4). The reason for interviewing is because of data saturation reason. Interviews with NGO authorities were also conducted.
The interviews aimed to understand the content of volunteers’ social networks (i.e., to identify the actual meaning, nature, and type of networks), and also to conceptualize concepts relevant to the study, such as pinpointing the actual significance of the volunteers’ work at the sampled NGOs. Initially, the interviews aimed to firstly identify the names and numbers of the NGOs where volunteering for Syrian refugees occurred, and then get the approval of relevant authorities to conduct the interviews. The interview data, then, helped to design the network-based questionnaire to be used consequently in a small survey. Selected volunteers were, then, asked about their social networks and social demographic information in the questionnaire. Data from the network survey was supported by interview data.
Table 2 demonstrates the format of the network questionnaire. It contained questions about individual volunteers’ socio-demographic details, the structure and types of social networks between the volunteers and their alters, the kinds of benefits (social capital) the volunteers obtained from their alters that helped in their volunteering work. For this article, “getting help” means the egos are getting “benefits” (social capital) from other volunteers (alters) who help them to do the volunteering work.
Sample of Questions of the Questionnaire.
In a typical social network analysis, including ego network analysis, the questionnaire is called a name-generator questionnaire. Therefore, this is unlike a typical survey questionnaire. The format of this name generator questionnaire is a roster format that allows the ego to name three alters who help them in volunteering in the NGOs. It contains two sections: (1) social demography data of the egos and (2) data on the egos’ networks with their alters. In the first section of the questionnaire, the egos were asked to tick the appropriate boxes regarding their social demographic characteristics including gender, age, and education. The second section of the questionnaire included two parts for the collection of the network data. The first part aimed to obtain network data on alters from egos directly. This part could provide data about direct ties that could, then, be used to explore the structure and type of egos’ networks, besides identifying benefits that the egos received because of the direct ties. The second part (for collecting network data) provided data about indirect ties that could be used in exploring the network structure, specifically on “structural holes.” In the study, egos are said to established direct ties with other volunteers (alters) if they directly did volunteering together. In comparison, alters who did not do volunteering together establish indirect ties. In short, in typical network language, direct ties mean ties established due to the conduct of doing activities together (in the study do volunteer activities together), while indirect ties mean no ties established for that reason.
For the authors’ study, indirect ties are equally significant as direct ties in explaining the social networks structure and the social capital findings, following the combined ideas from Burt’s structural hole theory and basic social network theory. Indirect ties created “holes” that in turn brought benefits for the volunteers (see Burt, 1992, 2000). The benefits, that is, social capital can be analyzed quantitatively using structural hole analysis. The findings are discussed in the coming section of this article.
Data Management and Analysis
In managing the data, the column-based wise format in the questionaire was exported as Excel files into an E-Net program (Halgin & Borgatti, 2012). In the EXCEL format, the data was organized in one matrix such that each row corresponded to a specific respondent (ego) and columns corresponded to ego attributes data, ego-alter ties and perceptions data, and alter-alter connections data see Table 3.
An Example of Extracted Network Data on All Volunteers (Egos) in the Hygiene Department Displayed in Column-Wise Format File in the Matrix Table Format in the Questionnaire.
Table 4 shows that the social demographic data was managed in the cells, as each cell in the matrix contained a value that represented the levels of measurement (interval and dichotomous). For example, the value for gender corresponded to a dichotomous measurement, where 1 = male and 2 = female. For network data, the matrix recorded ties between ego-alter and alter-alter for their volunteering activities through the use of 1s and 0s. Please refer to Table 3. If a volunteer (an ego) was tied with other volunteers (alters), it is recorded as (1). This (1) symbolizes the existence of a tie, meaning that the volunteer performs that behavior (e.g., taking assistance or guidance) with other volunteers. But if a volunteer is not connected with other friends, it is recorded as (0) in the cells. This means there were no ties between them, and that they thus did not do volunteering activities together.
Data On Social Demographic Characteristics of Volunteers (Egos) at YAO Displayed in the Column in the Matrix Table Format in the Questionnaire.
These findings can then be transformed into network graphs using a particular network graph computerized software called NetDraw (Borgatti et al., 2018). This means social network data, including indirect ties and structural holes in the networks can be mapped visually (see Figure 1).
Visiting ties for ego 3 in the hygiene department.
Figure 1 shows that ego3 has three direct ties with alter2, alter3, and alter4 and these ties are represented as dark solid lines. Also, there are indirect ties between alter2 and alter4, and these ties between alter2 and alter4 are represented as dark dotted lines. As a result, one can view the networks visually on paper in two-dimensional form. In the network graph, the links or ties between the nodes are called “lines.” So, one can see various lines linking various nodes to form a network. The more nodes and lines are there, the more complicated the network graph would be.
Social network analysis is the structural analysis of the patterning of social networks, of the linking between the network actors. It can analyze social networks qualitatively and quantitatively at the same time. For this study, qualitative social networks analysis is conducted upon semi-structured interviews using thematic analysis. As for quantitative social network analysis, it analyses systematically patterns of social relations or social networks to obtain quantitative network data. The analysis is conducted by a computerized software called E-NET (Borgatti, 2006).
Following Burt, for ego network analysis, indirect ties (“structural holes”) were analyzed quantitatively to obtain findings on the nature of indirect ties (different from previous studies analyzed direct ties). The analysis can gain data on constraints of the indirect ties and effective indirect ties. Both constraints and effective ties basically mean indirect ties can bring benefits, that is, social capital to the egos. Constraint and effective size measurements were used to measure quantitatively the level of indirect ties between alter and alter. This means the level of capital that the indirect ties provide to the egos.
The following section in this article shall discuss some findings on social network analysis of some egos (or volunteers) that produced an ego network structure of the volunteers’ networks with their alters, the types of social networks between them and the benefits that the egos received from their alters through the volunteering work. Various direct and indirect ties between the egos and alters, and between the alters were discovered. The discussions of the findings and analysis are as follows.
The Findings
The following sections elaborate on some key findings of the study. The findings are about the socio-demographic characteristics of the volunteers, the nature of social networks (i.e., ego networks structure and types of social networks) of the volunteers and outcomes of their networks in the form of social capital or benefits.
Social Demographics Characteristics of the Volunteers
Table 5 shows that the sample was 75% male and 25% female. The mean age of the volunteers was 33.4 years. Most of them had Bachelor’s degrees (55%). Furthermore, there were 75% Kurdish, 20% Kurdish-Syrian, and 5% Syrian among the volunteers. The most popular place of residence for the volunteers was camp (70%) and the others stayed in Slemani City (30%). This means that most of them were or lived with the Syrian refugees, but all of them were spoke Kurdish. Lastly, they held different positions at both organizations, specifically four “assessment and distribution” workers and one “team leader” at one NGO, four “mobilizers,” and one “hygiene promotion” worker in the hygiene department, and one “shopkeeper,” six “employees,” one “technician,” and two “foremen” in the wash and shelter department at another NGO. Based on the interviews, all of the volunteers had specific positions, but they volunteered to perform other activities as well depending on their selected jobs. In general, some key findings are uncovered, for instance, 100% of all the volunteers are Muslims and of Kurdish ethnicity. Although religion value and ethnicity are not part of structural analysis, they have been analyzed as descriptive analysis in the background of respondents. In social network analytic terms, their similarities in religious background and ethnicity would enable them to establish or even strengthened social networks between themselves for their volunteering. Consequently, they would gain value and benefit from their networks, namely in terms of social capital.
Social Demographics of Egos.
Social Network Structure of the Volunteers
The social network structures of the egos demonstrated the presence of those egos, their alters, direct ties (between the egos and their alters), and indirect ties (between the alters). The structure shows shared activities between the egos and alters (presence of ties). The structure also shows indirect ties among alters who did not conduct activities together (absence of ties). For better understanding of the findings, it provided an example as follows.
Figure 2 reveals that the network structure of ego 1 (e.g., at one of NGO) includes ego 1, the alters, direct ties between the ego and alters, and indirect ties between alters. Ego 1 and alters are represented as red diamonds. Direct ties are represented as dark solid lines and indirect ties are represented as dark dotted lines. Ego 1 is tied with each alter 1, alter 2, alter 3, and alter 4 directly. However, there is an indirect tie between alter 1 and alter 3, and an indirect tie between alter 3 and alter 4. In short, there are connections between ego 1 and alters, and between alters. These patterns of connections (who is linked with whom and who is not linked with whom) were considered as social networks which consist of the direct and indirect ties between the ego 1 and alters and between the alters. Such findings supported social network theory, which contends that having or lacking connections between people determines particular social network structures based on direct and indirect ties between the nodes (Weenig, 2004). The ego’s network structure helped him to depend on his/her alters in terms of volunteering or to carry out the activities more easily (Bruggeman, 2008; Burt, 1992; Coleman, 1988, 1994; Field, 2003). Such findings are supported by interview data. Given an example, ego9 in the wash and shelter department stated that direct and indirect are helpful him to do volunteering acivities:
“The volunteers are my frineds within the departments. I have strong ties with some of them. When I want to renovate or build shelters for the refugees and I need help to solve a problem during the work, I ask the volunteers who have strong ties with me. Also, I sometimes recieve assistance from volunteers who do not have direct ties with other volunteers, but they still present me assistance. Thus, I can complete the volunteered activity for the refugees because of having those ties”
Ego 1 network structure.
Thus, social network theory is supported: connected people can perform actions together more easily compared to doing them alone because their ties are paths of mutual influence (Borgatti & Ofem, 2010; Field, 2003).
Furthermore, this article uncovered one main type of social network which is friendship network. Egos are friends with all their alters, and similarly, all the alters are friends with other alters. All of them are in the same department of the organization, despite doing different kinds of volunteering work between themselves. They still are friends with each other although not doing volunteering together. Interviews with ego2 and ego4, interviews with ego1, ego2, and ego5 in the hygiene department and interviews with ego4, ego7, and ego9 in the wash and shelter department at both NGOs confirmed similar type of friendship networks among them. An interview with ego2 confirmed that the volunteers spent a lot of time together in one department, and thus, they are tied together as friends. The participant who was ego2 stated that “We have informal ties and out of formal rules at our formal environment (within the departments of the organizations).”
Social Networks as Social Capital for the Volunteers
Direct and indirect ties enabled the volunteers (nodes) in the network to do activities together—direct ties (presence of ties) mean that volunteers do volunteering activities together, while indirect ties (absence of ties) mean that volunteers do not do volunteering activities with other volunteers even though they have friendship ties. By using both direct and indirect ties, volunteers could get benefits. The egos gain benefits (social capital) from direct ties with alters and from indirect ties between alters that help them in their volunteering activities. As mentioned earlier, the social networks generate value in terms of social capital that is otherwise conceptualized and empirically proven as “benefits.” The benefits included task, informational, and social support benefits. Task benefits are in terms of giving assistance in building and renovating the refugees’ shelters and maintaining good hygiene and repair services in the shelters . Further, the egos received social support benefits from alters, which means they could enjoy time with each other to develop their friendship networks. The following sections explained the findings on the three types of benefits or rather social capital.
Social Capital in Terms of Information Benefits
Based on the interview data, the volunteers (egos) discussed necessary information and guidelines with alters related to conducting the hygiene seminars for Syrian refugees for example. The egos needed each other to share information such as how they should present the seminars to the refugees or how distribute non-food items. From the supporting network data, egos received guidance from alters about cooperation and preparing seminars. Moreover, the egos discussed with alters on doing activities. Some alters did not do these activities among themselves because they were more disconnected. Hence, the egos reaped most of the benefits (social capital gained) from interacting with the alters. For better understanding of the findings, it provided an example as following:
The network data in Figure 3 shows that ego 1 connected with alter 1 and alter 3. Ego 1 was able to discuss issues with alter 1 and alter 3 due to their direct ties. Coleman (1994) explains that direct ties between people allow them to receive information benefits, which helps guide their activities. Thus, based on Coleman, ego 1 and the alters discussed together through their direct ties, shared information and guidance (informational benefits) that fostered cooperation between them. With that information, the ego was able to present at hygiene seminars to the refugees. Also, ego 1 discussed the topic with alter 2, who did not have direct ties with alter 1 and alter 3 (Figure 3). Furthermore, Alter 2 did not have discussions with alter 1 and alter 3 because they were not connected. Rather, alter 2 discussed with ego 1. This means that the ego was able to obtain information and guidance from those alters, who did not discuss the topic amongst themselves. Thus, the indirect ties of alter 2 became a social capital (i.e., benefit) for the ego who conducted the seminars for the refugees (Burt, 1992). Moreover, ego 1 discussed the seminar with alter 2 before other alters discussed the matter. This is because alter 2 had no direct ties with other alters, thus the alter was only able to discuss with ego 1 directly. Also, the ego had a great opportunity to obtain information and guidance because ego1 had three sources of information (alter 1, alter 2, and alter 3), but the other alters had fewer sources of information than the ego. As ego1, in the hygiene department, in an interview stated that direct and indirect are crucial to get information benefit:
“I sometimes require other volunteers to share information such as how I should deliver the seminars to the refugees or which issues are crucial to conduct seminars on. I gather information from some sources including the volunteers who have strong ties with me. We discuss together. I receive information, the n, I present seminars with the rich information of the volunteers. Also, I receive information with volunteers who do not have strong ties with other volunteers, but they are a valuable resource to do the volunteered activity better.”
Discussion ties for ego 1 in the hygiene department.
Social Capital in Terms of Task benefits
From the supporting network data, egos obtained task benefits (social capital) through both direct and indirect ties as both communication and interaction. Egos communicated and interacted with alters for example discussed and planned together to renovate shelters and operate repair services in the shelters for Syrian refugees. Some alters did not do the activities together because of the indirect ties between them, so the egos got the benefits from these alters. Interviews with ego4, ego7, and ego9 revealed their similar views on the significance of direct and indirect ties to facilitate volunteering. For example, they explained that egos repaired broken doors with alters who had direct ties with them. The egos could take blocks, cement, or tools during building and renovating shelters from alters who did not tie with other alters directly; sometimes the ego needed to know how to repair a broken door, or the egos cooperated with the alters to receive assistance in building and renovating the refugee shelters.
Figure 4 revealed that ego 2 connected with alter 2, alter 5, and alter 6; he asked the alters his questions (Figure 4). The alters gave assistance to the ego because of their direct ties with him (Coleman, 1994); Coleman explains that through direct ties people are connected such that they can help one another to accomplish their tasks. Hence, the ego’s direct ties with the alters allowed the ego to receive assistance from them. Once he received the assistance he could solve the problems and then provided the repair services to the refugees.
Ties based on asking information from other volunteers for ego 2 in the wash and shelter department.
In addition, ego 2 cooperated with alter 6, who did not connect with alter 5 or alter 7. Alter6 did not cooperate with alter 5 and 7 because he had no direct ties with them. Rather, the alter cooperated with ego 2, which means that the ego received assistance from alter 6. The finding is supported by Burt (1992), who believes that a person can get benefits from others who have no direct ties between them in terms of both opportunity and timing. Moreover, in line with Burt’s argument, the ego was able to discuss with alter 6 sooner than with alter 5 and alter 7. This is because alter 6 did not have any ties with the other alters and thus did not get assistance from them. The earlier response from alter 6 could help the ego to complete his volunteering activity sooner. Also, the ego had a greater opportunity to obtain benefits (from three sources) while the alters had less. More ties provided greater benefits (see Burt, 1992). The ego was able to build and/ or renovate the shelters because of his/her direct ties with alter 5 and alter 7 and the indirect ties between alter 6 and the other two alters. Ego7 in the wash and shelter department in an interview stated that ties (direct and indirect) are helpful to provide task benefits:
“I ask volunteers who have strong ties with me to assist in solving problems related to electricity or welding while providing repair services such as for windows and doors in refugees’ shelters. Once I receive the help, I can solve the problem and repair the refugee’s door or window. Besides obtaining benefit because of strong ties, I obtain benefits from volunteers who do not have strong ties with other volunteers because they do not offer assistance for each other, thus, I get benefits. This means I can do volunteering activities for the refugees.”
Social Capital in Terms of Social Support Benefits
Social capital in terms of social support benefits have been obtained through both direct ties and indirect ties (social networks). The benefits are in terms of developing friendship networks that had helped the volunteers (egos) in their volunteering. Interview data further supports these findings especially with ego1, ego2, ego4, ego7, and ego9. Egos developed friendship networks with their alters by gathering together and participating with their alters in social activities. That enabled the egos to obtain social support benefits from their alters, which in turn helped them in their volunteer work. Egos met up socially with alters; they participated in social activities together, such as going out together. In comparison, some alters did not meet up with alters because they had only indirect ties between them; then, the egos received all the social support benefits from them. For a better understanding of the findings, it provided an example as follows.
As shown in Figure 5, ego 3 with alter 2 and alter 3 visited each other at home. The ego and alters visited each other because of the direct ties between them (Coleman, 1994). When the ego and alters visited each other’s homes, they had enjoyed spending free time together. They developed their friendship which helped them to do their volunteering together. This finding is again supported by the theory; people gather with each other through direct ties in which they interact together and enjoy their time with each other (sociability); they develop their networks, which help them to act together (Allan, 1989; Coleman, 1994; García & Tegelaars, 2019; Wasserman & Faust, 1994).
Visiting ties for ego 3 in the hygiene department.
Furthermore, ego 3 visited alter 4, who did not visit alter 2 or alter 3 (Figure 5). Alter 4 visited the ego instead of visiting alter 2. This is a benefit (social capital) for the ego, as Burt (1992) believes that a person obtains benefits from other people who have no direct ties (or social networks) between them. The ego enjoyed spending free time together during the visits. They developed their friendship which helped them to do their volunteering together. In an interview, ego2 explained the important of direct and indirect ties in social support benefits:
“I go out or participate in social events such as picnics with volunteers who have strong ties with me. We enjoy spending time eating lunch/ during the event. We develop our friendship, which helps us do our volunteering work together as well. I sometimes go out with volunteers who do not have direct ties with other volunteers. They spend time with me because they do not go out with others. Thus, I enjoy time and develop friendship with those volunteers too. My developed ties benefit me to do volunteering for refugees as well.”
Lastly, the argument that the volunteers’ (egos’) social networks had generated social capital in terms of the three kinds of benefits discussed earlier is further confirmed through structural holes measurement created by Burt (1992) in ego network analysis. The structural holes quantitatively measured the presence of value or rather social capital (the three benefits) created by the volunteers’ indirect ties or social networks in terms of ties constraints and effective size indices. To elaborate, the findings revealed that all the volunteers’ indirect social networks have been shown to generate value or social capital for those volunteers concerned. This means that is it confirmed that the volunteers had received three types of benefits from all their indirect ties between all their alters in the networks.
Specifically, ego network analysis has statistically analyzed the structural holes between the alters that generated social capital or benefits for the egos. The analysis showed the varying levels of social capital for all the egos (see Table 6). From the table, one can see that egos have values between 0 and 1. Hence, values that are less than 1 mean that there are indirect ties between the alters merely because they did not do volunteering activities together. But for Burt, these indirect ties generated social capital (benefits) for the egos. The table also showed the values for effective size index. Some egos had high values compared to other egos; this implies that those egos were able to obtain more benefits compared to those other egos. This also means that there were more indirect ties between the egos’ alters compared to other alters who were linked to other egos, and following Burt (1992), more indirect ties between the alters means more benefits for the egos concerned.
Structural Hole Measure for Egos.
Conclusion
This article has presented and discussed some findings from a recent study on social networks and social capital for volunteering for Syrian refugees in Slemani City, Kurdistan region. The findings confirmed that direct and indirect social networks between some volunteers had generated social capital for them and consequently, motivated them to continue their challenging volunteering work for the Syrian refugees in Slemani City. How did the social networks actually produce social capital for the volunteers is confirmed at the conceptual, theoretical, methodological, and empirical levels.
Firstly, the authors conceptualized, and then operationalized and measured social networks and social capital. Social network theory, social capital theory by Coleman, and structural theory by Burt is the basis of the conceptualization, operationalization, and measurement. Putnam’s social capital further supported. Secondly, the authors employed social network analysis methodology to conduct a structural analysis of the structure and an ego-network analysis of patterning direct and indirect social networks between the volunteers, that is, who was linked to who in doing volunteering work, and who gets what benefits (social capital) from who during their volunteering work. The methodology is based on basic social network analysis as well as Burt’s structural holes analysis of indirect ties that produce social capital.
The social networks were found to generate social capital because they had added value and hence provided particular benefits to the volunteers namely task, informational and social support benefits. The structural analysis of the social networks between the volunteers revealed that they were both directly and indirectly linked to one another through friendship ties. The structural analysis also demonstrated how those networks had generated capital for the volunteers. Furthermore, by using both direct and indirect ties, the volunteers were able to obtain the capital or benefits from their networks. Task benefits are seen in terms of the assistance given by other volunteers to them such as building and renovating shelters for the refugees and maintaining good hygiene and tool services in the shelters. Informational benefits are in terms of obtaining information for cooperation and advice giving, and conducting seminars and campaigns for the refugees. In addition, the volunteers received social support benefits from the other volunteers they networked while doing similar volunteering. The benefits were obtained through social gatherings. These findings had contributed to the study and operation of NGOs for refugees by proving the key role of social networks in generating social capital for the volunteers and subsequently, motivating the volunteers, NGOs, agencies, and government to continue pursuing their volunteering for the refugees and assisting them even in tough conditions and environments. For future studies, a whole network study design can be applied. This design will resolve the small sampling issue. Furthermore, future studies can also be conducted to explain how social networks become social capital for volunteers who help asylum-seekers, displaced people, or immigrants in different social contexts.
Footnotes
Author Note
This research was conducted while Taban Khalid Ahmed was at Universiti Kebangsaan Malaysia. She is now at University of Sulaimani and may be contacted at
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by Fakulti Sains Sosial dan Kemanusiaan, Universiti Kebangsaan Malaysia.
