Billions of people create trillions of connections through social media each day, but few of us consider how each click and key press builds relationships that, in aggregate, form a vast social network. Passionate users of social media tools such as email, blogs, microblogs, and wikis eagerly send personal or public messages, post strongly felt opinions, or contribute to community knowledge to develop partnerships, promote cultural heritage, and advance development. Devoted social networkers create and share digital media and rate or recommend resources to pool their experiences, provide help for neighbors and colleagues, and express their creativity. The results are vast, complex networks of connections that link people to other people, documents, locations, concepts, and other objects. New tools are now available to collect, analyze, visualize, and generate insights from the collections of connections formed from billions of messages, links, posts, edits, uploaded photos and videos, reviews, and recommendations. As social media have emerged as a widespread platform for human interaction, the invisible ties that link each of us to others have become more visible and machine readable. The result is a new opportunity to map social networks in detail and scale never before seen. The complex structures that emerge from webs of social relationships can now be studied with computer programs and graphical maps that leverage the science of social network analysis to capture the shape and key locations within a landscape of ties and links. These maps can guide new journeys through social landscapes that were previously uncharted.
In the twenty-first century, network science has blossomed alongside a new global culture of commonplace networked communications. With widespread network connectivity, within just the past few decades, billions of people have changed their lives by creatively using social media. We use social media to bring our families and friends closer together, reach out to neighbors and colleagues, and invigorate markets for products and services. Social media are used to create connections that can bind local regions and span continents.
These connections range from the trivial to the most valued, potent collaborations, relationships, and communities. Social media tools have been used successfully to create large-scale successful collaborative public projects like Wikipedia, open source software used by millions, new forms of political participation, and scientific collaboratories that accelerate research. Unheard of just a few years ago, today systems such as blogs, wikis, Twitter, and Facebook are now headline news with social and political implications that stretch around the globe. Despite the very different shapes, sizes, and goals of the institutions involved in social media, the common structure that unifies all social media spaces is a social network. All of these systems create connections that leave traces and collectively create networks.
The Rise of Social Media
Social media are visible in the form of consumer applications such as Facebook and Twitter, but significant use of social media tools takes place behind the firewalls that surround most corporations, institutions, and organizations. Inside these enterprises employees share documents, post messages and engage in extensive discussions, document annotation, and create extensive patterns of connections with other employees and other resources.
Social media tools cultivate the internal discussions that improve quality, lower costs, and enable the creation of customer and partner communities that offer new opportunities for coordination, marketing, advertising, and customer support. As enterprises adopt tools like email, message boards, blogs, wikis, document sharing, and activity streams, they generate a number of social network data structures. These networks contain information that has significant business value by exposing participants in the business network who play critical and unique roles.
Some employees act as bridges or brokers between otherwise separated segments of the company. Others have patterns of connection that indicate that they serve as sources of information for many others. Social network analysis of organizations offers a form of MRI or x-ray image of the organizational structure of the company. These images illuminate the ways the members of the organization are actually structured in contrast to the formal hierarchies.
Individual Contributions Generate Public Wealth
Collections of individual social media contributions can create vast, often beneficial, yet complex social institutions. Seeing the social media forest, and not just the trees, branches, and leaves, requires tools that can assemble, organize, and present an integrated view of large volumes of records of interactions. Building a better view of the social media landscape of connection can lead to improved user interfaces and policies that increase individual contributions and their quality. It can lead to better management tools and strategies that help individuals, organizations, and governments to more effectively apply social media to their priorities.
However, dangerous criminals, malicious vandals, promoters of racial hatred, and oppressive governments can also use social media tools to enable destructive activities. Critics of social media warn of the dangers of lost responsibility and respect for creative contributions, when vital resources are assembled from many small pieces. These dangers heighten interest in understanding how social media phenomena can be studied, improved, and protected. Why do some groups of people succeed in using these tools while many others fail? Community managers and participants can learn to use social network maps of their social media spaces to cultivate their best features and limit negative outcomes. Social network measures and maps can be used to gain insights into collective activity and guide optimization of their productive capacity while limiting the destructive forces that plague most efforts at computer-mediated communications. People interested in cultivating these communities can measure and map social media activity in order to compare and contrast social media efforts to one another.
Around the world, community stakeholders, managers, leaders, and members have found that they can all benefit from learning how to apply social network analysis methods to study, track, and compare the dynamics of their communities and the influence of individual contributions. Business leaders and analysts can study enterprise social networks to improve the performance of organizations by identifying key contributors, locating gaps or disconnections across the organization, and discovering important documents and other digital objects. Marketing and service directors can use social media network analysis to guide the promotion of their products and services, track compliments and complaints, and respond to priority customer requests. Community managers can apply these techniques to public-facing systems that gather people around a common interest and ensure that socially productive relationships are established. Social media tools have become central to national priorities requiring government agency leaders to become skillful in building and managing their communities and connections. Governments at all levels must learn to optimize and sustain social media tools for public health information dissemination, disaster response, energy conservation, environmental protection, community safety, and more.
Social Network Analysis
Social network analysis is the application of the broader field of network science to the study of human relationships and connections. Social networks are primordial; they have a history that long predates systems like Facebook and Friendster, and even the first email message. Ever since anyone exchanged help with anyone else, social networks have existed, even if they were mostly invisible. Social networks are created from any collection of connections among a group of people and things.
Social network analysis helps you explore and visualize patterns found within collections of linked entities that include people. From the perspective of social network analysis, the treelike “org-chart” that commonly represents the hierarchical structure of an organization or enterprise is too simple and lacks important information about the cross connections that exist between and across departments and divisions. In contrast with the simplified tree structure of an org-chart, a social network view of an organization or population leads to the creation of visualizations that resemble maps of highway systems, airline routes, or rail networks
Network analysts see the world as a collection of interconnected pieces. Those studying social networks see relationships as the building blocks of the social world, each set of relationships combining to create emergent patterns of connections among people, groups, and things. The focus of social network analysis is between, not within people. Whereas traditional social science research methods such as surveys focus on individuals and their attributes (e.g., gender, age, income), network scientists focus on the connections that bind individuals together, not exclusively on their internal qualities or abilities. This change in focus from attribute data to relational data dramatically affects how data are collected, represented, and analyzed. Social network analysis complements methods that focus more narrowly on individuals, adding a critical dimension that captures the connective tissue of societies and other complex interdependencies.
Once a set of social media networks has been constructed and social network measurements have been calculated, the resulting data set can be used for many applications. For example, network data sets can be used to create reports about community health, comparisons of subgroups, and identification of important individuals, as well as in applications that rank, sort, compare, and search for content and experts. The value of a social network approach is the ability to ask and answer questions that are not available to other methods. This means focusing on relationships. Although analysts, marketers, and administrators often track social media participation statistics, they rarely consider relationships. Traditional participation statistics can provide important insights about the engagement of a community, but can say little about the connections between community members. Network analysis can help explain important social phenomena such as group formation, group cohesion, social roles, personal influence, and overall community health.