Starting in the early twentieth century, social scientists began to explore how people are connected to one another and how these connections influence their everyday lives. Social network analysis (SNA) is a tool for measuring and visualizing the structure of social relationships between two or more people. Using a questionnaire, researchers ask respondents to name who within a given community they look to for information, advice, support, and so on. These data are then used to study adolescent risk behaviors, information diffusion, corporate behavior, and many other topics (Abrutyn and Mueller 2014; Pedulla and Pager 2019).
Figure 2.2 is a network diagram of friendships among twelve-year-old students in one sixth-grade class. Each colored dot is a girl (red) or boy (blue) in the class, and the arrows represent social ties. As you can see, the girls are almost exclusively friends with other girls, as are boys with other boys. Looking at the cluster of girls, you see a few girls with a lot of arrows pointing to them. This means that many other students identified these girls as their friends. The more arrows pointing in, the more popular—or “central”—that person is within the network.
Another important position within this network is those students who link the boys and girls to one another. These “bridges” enable information to flow between the groups (also called “cliques”). It is worth noting that only girls identified boys as friends; no boys identified girls as friends (as shown by the directionality of the arrows). Thus, we can say that these ties lack reciprocity, meaning the arrows, or connections, flow in only one direction. Finally, every member of this network is connected in about three steps or has an average of three degrees of separation from every other member. Researchers use these types of data to understand how social networks influence substance abuse, bullying and victimization, and delinquency and to design interventions to address adolescent issues.
FIGURE 2.2Network Diagram of Friendships among Students in One Sixth-Grade ClassSOURCE: Valente 2015.
With the advent of social media, especially Facebook in the early 2000s, “social network” became a household phrase. While many people today mistakenly think that SNA began with the study of online social networks, it well predates the internet. Some of the earliest work in the area of SNA began with sociologist Georg Simmel, who studied social ties among members of a community and how the size of a group affects the relationships among its members, or actors. In the late 1960s, Stanley Milgram’s work on the “small world” phenomenon brought publicity to the field; his studies showed that everyone is connected by an average of five and a half to six steps to everyone else in the world (Travers and Milgram 1969). This phenomenon was later termed the “six degrees of separation.” The advent of computer programs for analyzing networks helped create a large, diverse field that incorporates scientists from varying disciplines, including sociology, anthropology, political science, medicine, physics, and computer science.
Social network programs have now been created to study large-scale networks such as Instagram, Facebook, Twitter, Snapchat, and LinkedIn. Today, social network researchers can study Twitter feeds and other social media sites to discover patterns of communication between and within terrorist groups in order to disrupt their activities (Everton 2012). Studies of social media are also being conducted to better understand the flow of information, the nature of political discourse, and types of civic engagement. One such study looked at how organizers of the Occupy Wall Street movement used Twitter to organize and spread the movement (Tremayne 2014). More recently, sociologists have used social network analysis to map the spread of Covid-19; these analyses can aid preparation and prevention efforts (Weeden and Cornwell 2020).
Advantages and Disadvantages
ADVANTAGES
Social network analysis can trace the route of just about anything—an idea, disease, rumor, or trend—as it moves through a social group, community, or society. This makes SNA a useful method for epidemiologists (scientists who study diseases within populations), political sociologists, and market researchers.
Social network analysis often uses “big data”—data sets so large that typical computer and storage programs cannot handle them—which has become increasingly popular in both the academic and the business worlds. Big data enables corporations to identify major trends quickly, target audiences effectively, and make predictions. Big data also creates new fields of research for social scientists (Lazar et al. 2009).
DISADVANTAGES
Social network analysis, because it is often quantitative, can gloss over important details and diversity in the experiences of social actors. Combining social network analysis with qualitative methods can help overcome this problem. For example, Harvard sociologist Mario Small, in his 2019 book Unanticipated Gains, uses mixed methods, both qualitative and quantitative, to chart the effects of participation in child-care centers on the social networks of New York City families.
Big data is expensive to collect and analyze, and large social network data sets often come from sources that have been assembled for other purposes (such as advertising) or that pose a threat to privacy.
SOCIAL NETWORK ANALYSIS
Starting in the early twentieth century, social scientists began to explore how people are connected to one another and how these connections influence their everyday lives. Social network analysis (SNA) is a tool for measuring and visualizing the structure of social relationships between two or more people. Using a questionnaire, researchers ask respondents to name who within a given community they look to for information, advice, support, and so on. These data are then used to study adolescent risk behaviors, information diffusion, corporate behavior, and many other topics (Abrutyn and Mueller 2014; Pedulla and Pager 2019).
Figure 2.2 is a network diagram of friendships among twelve-year-old students in one sixth-grade class. Each colored dot is a girl (red) or boy (blue) in the class, and the arrows represent social ties. As you can see, the girls are almost exclusively friends with other girls, as are boys with other boys. Looking at the cluster of girls, you see a few girls with a lot of arrows pointing to them. This means that many other students identified these girls as their friends. The more arrows pointing in, the more popular—or “central”—that person is within the network.
Another important position within this network is those students who link the boys and girls to one another. These “bridges” enable information to flow between the groups (also called “cliques”). It is worth noting that only girls identified boys as friends; no boys identified girls as friends (as shown by the directionality of the arrows). Thus, we can say that these ties lack reciprocity, meaning the arrows, or connections, flow in only one direction. Finally, every member of this network is connected in about three steps or has an average of three degrees of separation from every other member. Researchers use these types of data to understand how social networks influence substance abuse, bullying and victimization, and delinquency and to design interventions to address adolescent issues.
With the advent of social media, especially Facebook in the early 2000s, “social network” became a household phrase. While many people today mistakenly think that SNA began with the study of online social networks, it well predates the internet. Some of the earliest work in the area of SNA began with sociologist Georg Simmel, who studied social ties among members of a community and how the size of a group affects the relationships among its members, or actors. In the late 1960s, Stanley Milgram’s work on the “small world” phenomenon brought publicity to the field; his studies showed that everyone is connected by an average of five and a half to six steps to everyone else in the world (Travers and Milgram 1969). This phenomenon was later termed the “six degrees of separation.” The advent of computer programs for analyzing networks helped create a large, diverse field that incorporates scientists from varying disciplines, including sociology, anthropology, political science, medicine, physics, and computer science.
Social network programs have now been created to study large-scale networks such as Instagram, Facebook, Twitter, Snapchat, and LinkedIn. Today, social network researchers can study Twitter feeds and other social media sites to discover patterns of communication between and within terrorist groups in order to disrupt their activities (Everton 2012). Studies of social media are also being conducted to better understand the flow of information, the nature of political discourse, and types of civic engagement. One such study looked at how organizers of the Occupy Wall Street movement used Twitter to organize and spread the movement (Tremayne 2014). More recently, sociologists have used social network analysis to map the spread of Covid-19; these analyses can aid preparation and prevention efforts (Weeden and Cornwell 2020).
Advantages and Disadvantages
ADVANTAGES
DISADVANTAGES