The Handbook of Conflict Resolution (3rd ed)

by Peter T Coleman

  TRADITIONAL SOCIAL NETWORK ANALYSIS

  Social network concepts allow us to methodologically describe the structural linkages among entities (Newman, 2003; Wasserman and Faust, 1994). Figure 41.1a illustrates a traditional social network analysis of a small social network interacting around a working and a stay-at-home spouse. In this illustration, five individuals have various links with one another. These charts have considerable appeal for describing basic connections among people, and social scientists have generated an array of statistics to describe the interactions in these case studies (Balkundi and Kilduff, 2006). For instance, the concept of density indicates the number of observed links divided by the number of total possible links in the network. In figure 41.1a, there are four links divided by ten possible linkages, which results in a network density of .40. When this number approaches 1, it represents a network where everyone is densely connected to one another and implies a strong form of interdependence. When the metric is near 0, it illustrates a social network where no one is connected and implies independence among actors.

  Figure 41.1 Network Chart Comparisons

  Sociologists have developed other metrics to describe social networks as well (Wasserman and Faust, 1994). For example, centrality typically represents how information flows through central individuals in social networks. In figure 41.1a, you can see that the working and stay-at-home spouses are more centrally located in the network than others. When the centrality indicators approach 1, it often suggests that information is flowing through key individuals in the system, such as the spouses in this case. Another important conceptualization in the social network literature is that of structural holes (Burt, 1992), which represent “gaps in the social world across which there are no current connections, but that can be connected by savvy entrepreneurs who thereby gain control over the flow of information across the gaps” (Kilduff and Tsai, 2003, p. 28). The concept that weak links can be powerful (Granovetter, 1973) also illustrates situations where people can leverage their weak contacts with others to facilitate social capital in their lives. For example, by engaging in even a brief conversation with your new neighbor, you could create a weak link, which may facilitate your social capital in the future. However, this line of theorizing does not sufficiently differentiate how various types of links may have different effects (e.g., a weak hostile link could have an adverse impact on such capital), which can be important according to dynamic network theory (Westaby, 2012).

  The principle of homophily is relevant to some conflict settings as well. Homophily often refers to the tendency for people to interact and connect with similar others. Kupersmidt et al. (1995) showed how similarity between individuals increased their likelihood of being friends. In contrast, the ties between people that are not similar to one another are more vulnerable to decay, which can set the stage for social niches to form (McPherson, Smith-Lovin, and Cook, 2001). However, such dissimilarity need not always lead to conflict. Dynamic network theory (Westaby, 2012) illustrates that there are many situations in which people are willing to work with and support others that are not similar to themselves in pursuit of common goals.

  Finally, in line with assumptions that people are motivated to maintain structural balance in their interpersonal relations and cognitions (Cartwright and Harary, 1956), researchers often look at the generic positive and negative valences people have with one another and then make assumptions about the entire system. In other words, if we know how many positive and negative links exist in a social network, we may presume that we can understand how much overall conflict and cooperation there is in the system. For example, in 41.1a, you can easily see that the working and stay-at-home spouses have a negative relation with each other (the dashed path), which implies an interpersonal conflict. All other linkages have positive valences in the system (the solid paths). From this orientation, the ratio of positive to negative valences is .75 in this example, implying a generally positive system of interpersonal relations. Although mapping valences in this way is a common approach for studying interpersonal relations and is presumed to model the true motivational forces of full systems, it has the potential to oversimplify the underlying motivational and conflicting forces in the network. Dynamic network theorizing that incorporates goals provides an alternative perspective as illustrated below. Overall, traditional social network perspectives benefit both researchers and practitioners of conflict resolution by encouraging the assessment of conflict in broader social systems instead of focusing on the primary parties involved in the conflict.

  SOCIAL NETWORK RESEARCH ON CONFLICT

  We now review research findings regarding traditional networks and conflict. Although not an exhaustive review, this includes a sampling of research at different levels of analysis. First, in a study of 2,348 married or cohabitating adults, Walen and Lachman (2000) found that networks with higher levels of support reduced harmful effects during strained interactions. They also found that women benefited more from friends and family than men did. From another vantage, Vanbrabant et al. (2012) found a positive association between personal social network size and reported verbal aggression, controlling for extraversion, neuroticism, and gender. Neal (2009) examined the peer social networks of third through eighth graders, looking specifically at the location of aggressive children in terms of network centrality and density and how these variables were associated with relational aggression. Results indicated that network density was positively related to relational aggression. In contrast, in a study of sixth graders, Mouttapa, Valente, Gallaher, Rohrbach, and Unger (2004) found that children who were friends with a bully (self-reported) were more likely to self-report bullying behavior themselves and less likely to report being a victim of bullying.

  Social network analysis has been applied to understanding a variety of negative group dynamics as well. One study examined conflict within groups in terms of adversarial networks (Xia, Yuan, and Gay, 2009). Not surprisingly, these researchers found that group members who have more negative evaluations of other group members are less satisfied with the group. As for psychological dynamics in groups, research has shown that task conflicts can have a positive effect on groups performing complex tasks as compared to routine tasks, but relationship conflicts have a negative effect (Jehn, 1995). Curşeu, Janssen, and Raab (2011) extended these findings by identifying network structures that minimize destructive conflict in groups. They suggest that work groups can maximize the benefits of conflict in teams by dividing groups into subgroup task units while minimizing the destructive elements of relationship conflict through training in communication and interpersonal skills.

  de Dreu and Gelfand (2008) have pointed out that organizations today operate in an interorganizational network that has a strong influence on personnel selection, managerial techniques, and technologies, all of which play a role in conflicts and tensions in an organization. These conflicts often manifest internally as environmental pressures exert uneven influences on different aspects of the organization. As for leadership in organizations, Balkundi, Barsness, and Michael (2009) found that leaders who were frequently sought out for advice reported lower incidents of team conflict.

  Labianca, Brass, and Gray (1998) found that individual perceptions of high intergroup conflict in an organization were related to negative relationships across groups, indirect negative relationships through friends in the organization, and low intragroup cohesiveness. Using simulations, Krackhardt and Stern (1988) found that organizations with a higher density of friendship links that extended across subgroups outperformed those where friendship networks were most dense within subgroups.

  SOCIAL MEDIA

  The past two decades have seen unprecedented innovation in social media technology and services that facilitate digital communication between individuals, groups, organizations, and nations. According to Hughes, Rowe, Batey, and Lee (2012), “social networking sites (SNS) are quickly becoming one of the most popular tools for social interaction and information exchange�
�� (p. 561). For instance, at the time of this writing, among all US adults, 66 percent use at least one social networking site (e.g., Facebook, LinkedIn, or Google+), and 48 percent visit these sites as part of their typical day. Facebook, launched in 2004, is currently the most popular digital social networking service. As of September 2012, the number of monthly active users of Facebook worldwide reached 1 billion, with Brazil, India, Indonesia, Mexico, and the United States being the top five countries in terms of membership numbers (Facebook, 2012). That means that roughly one in seven global citizens is using the service in some capacity. Twitter is also a popular social media website, and it is likely that a variety of new services will emerge in the future as competition increases in this expanding market. Although there are reasons to suspect that these online tools would reduce conflict through increased social interaction and the ability to express views regardless of geographic location or social stratus, it is also likely that the increased availability of these communication tools, combined with the ability to remain anonymous, may serve the opposite effect (Bargh and McKenna, 2004).

  Early experimental research on computer-mediated communication showed that users participated more equally, were able to more quickly shift positions on topics or decisions, and were less inhibited than when communicating face-to-face (Kiesler, Siegel, and McGuire, 1984). Today there are countless spaces online where individuals can form virtual groups for discussion and sharing ideas, including places to help resolve conflicts. While many of these groups may function well, there are frequent examples of online interactions that escalate into destructive, counterproductive dialogues (Lee, 2005; Moor, Heuvelman, and Verleur, 2010). Lee (2005) has illustrated various ways that social media users deal with hostile situations online, such as competitive strategies (e.g., flaming and denouncing), avoidance approaches (e.g., withdrawal), and cooperative tactics (e.g., showing solidarity, apologizing, and mediating).

  Some research has shown how online social networks can complicate relationships. For example, Papp, Danielewicz, and Cayemberg (2012) found that disagreements among couples as to whether the relationship status should be shared on Facebook was associated with decreased relationship satisfaction for women but not men. Some researchers suggest that sites such as Facebook also make it easier for an individual to obsessively observe someone without his or her consent, especially the case for former romantic partners (Chaulk and Jones, 2011; Lyndon, Bonds-Raacke, and Cratty, 2011), as well as promote jealousy in current relationships due to online monitoring of the partner’s activities (Muise, Christofides, and Desmarais, 2009).

  Cyberbullying is also becoming a serious concern. Mesch (2009) reported that adolescents who have active profiles on social networking sites or who participate in online chat rooms are more likely to be bullied. In a survey of 756 Turkish middle school students, males indicated engaging in more cyberbullying than females, and students were often not aware of effective strategies for bringing cyberbullying issues to adults (Yilmaz, 2011).

  Defamation on the Internet and on social media is another serious source of conflict and interpersonal hardship, and there are few standardized ways to deal with its presence. For example, some individuals may take advantage of freedom of speech values (e.g., implicitly or explicitly endorsed by a website’s policy) by making false accusations about others in efforts to tarnish or destroy their reputations. Some may even do so to promote their competing products or ideology. This is often made possible when website platforms do not sufficiently vet posted information or do not remove abusive information, have insufficient guidelines to avoid defamatory situations, and do not verify (or post) true identities. Complicating matters further is when such defamatory accusations are made anonymously without verifiable evidence. In such cases, it is difficult to hold the accusers accountable for their commentary, which may remain online indefinitely. Some of the ways that people could manage these escalated situations is to pursue legal action against the websites or the individuals posting such material online (if they can be identified through court action or digital tracking). This can be a costly and emotionally laborious process. Various people have described the current state of affairs on the Internet as the “wild west” (Hundley and Anderson, 1995), which implies that some people may become victimized by others who exploit systems or take advantage of poor accountability. A related issue of conflict concerns privacy of information. Given that communications and images are held in digital form online, conflicts arise in terms of how that information is used by third parties. Large-scale conflicts can arise when important digital information is lost, stolen, or sold without permission.

  Relevant to new advances in online gaming technology, Ferguson (2010) highlights the implications of massive multiplayer online role-playing games (MMORPG). These games often include violence toward fictional characters, but at the same time promote complex social interactions between individuals, even individuals who would otherwise be challenged in social situations, which allows whole online social communities to develop. However, because research has shown that violence on TV can affect aggressive behavior (Bushman and Huesmann, 2006), much more research is needed to evaluate MMORPGs.

  Even basic e-mail conversations can contribute to the escalation of network conflicts. Friedman and Currall (2003) suggest that the nature of e-mails is asynchronous, which means that e-mail correspondence is not a conversation but instead a back-and-forth exchange of statements. It is also text based, which means it lacks the facial expressions of face-to-face or videoconferencing interactions and verbal intonation and nuance that would be present in a telephone conversation. This can contribute to misunderstanding. However, e-mail allows people to delay responses and take more time to review and revise their messages for accuracy. Turnage (2007) suggests several ways to deal with these pitfalls such as “netiquette” training programs.

  In communities around the globe, many youth represent the wired generation of individuals who have connected and engaged in ways never before possible, which allows entirely new ways of organizing and exercising participatory citizenship roles (Herrara, 2012). Social media may also play an important role in how citizens take action when they become dissatisfied with their governments. For example, in Egypt, early social media use among youths was primarily in the form of blogging. The extreme popularity of blogging was soon supplanted by the introduction of Facebook, which saw membership grow from a little over 800,000 in 2008, to 5.6 million three years later, with 2 million users joining Facebook during the first few months of the Arab revolutions (Herrera, 2012). Facebook may have allowed many youth to organize much more effectively than blogging because of the ability of individuals to create groups, Facebook pages for various issues, and mass invites for Facebook members to attend events (such as sit-ins, protests, marches, and strikes). In addition, Twitter may have provided protestors with an effective way of quickly engaging foreign media, and the media were able to provide more comprehensive and moment-to-moment reporting of events in real time (Lysenko and Desouza, 2012).

  Online communication tools such as Twitter also offer a promising new platform for researchers to explore large-scale conflict dynamics. Not only are various forms of data publicly available, but the data often represent an aspect of the actual network of communications characterizing the situation. Scholars can use these data to analyze international conflicts dynamically because people on the ground are disseminating information about events that are occurring in their communities in real time. For example, Zeitzoff (2011), using content from Twitter and other social media sources, was able to measure the military responses of Israel and Hamas during the 2008–2009 Gaza conflict to identify important turning points in the conflict: the movement of Israeli troops into Gaza and the UN Security Council vote calling for an immediate cease-fire. As social media tools proliferate, researchers will have more opportunities to conduct studies like this, mapping complex large-scale conflict dynamics as they unfold.

  DYNAMIC NETWORK TH
EORY

  Although traditional social network concepts have been incredibly helpful in showing how people are linked to one another in various ways, they have lacked a deeper integration of psychologically based goal pursuit and intention concepts, which are often presumed to be critical drivers of human action (Ajzen, 1991; Westaby, 2005; Westaby, Probst, and Lee, 2010). This psychological void may be a concern because many human conflicts result from tensions originating with people’s opposing goals, desires, and aspirations (Deutsch, 1977). Hence, accounting for goals in social networks is critical to advancing our understanding of how conflicts can be addressed and resolved. Fortunately, new advances in the dynamic network theory of goal pursuit (Westaby, 2012) explicitly address how social networks are involved in fundamental goal pursuits, which has implications for the study of conflict and its resolution.

  What’s New and Different?

  A unique feature of dynamic network theory (Westaby, 2012) is that it articulates how only eight social network role behaviors are critical to explain how social networks are involved in goal pursuits and human aspiration. We illustrate these roles in the context of a network having a work-family conflict generated by a working spouse with a strong desire or goal to work a lot of overtime. In this case, the working spouse is considered a goal striver toward working overtime (G) in the theory. The spouse is also receiving a lot of support for working overtime from a supervisor and other coworkers at the firm (who are perhaps swamped at work). These entities are referred to as system supporters (S) in the theory. These linkages and their labels can be seen in the dynamic network chart in 41.1b. The theory predicts that systems that have considerable goal striving and system supporting (more generally referred to as network motivation) will have higher levels of success in reaching their target goal, especially when they are competent in their actions.