More about Social Network Mapping
To understand social network mapping in user research, it is essential first to grasp the concept of social networks. A social network is a platform, physical or digital, where individuals connect as friends, family, colleagues, or people sharing common interests, beliefs, social status, or other interdependencies. In these networks, individuals are known as nodes, while the connections or relationships between them are called ties.
A social network map helps visualize these nodes and ties, allowing researchers to identify patterns in interactions across the network. This mapping reveals influential actors or groups who play key roles in facilitating product adoption, spreading information, gathering insights, and supporting various phases of a design project. By analysing how social networks operate, whether zooming in on a household or scaling out to a global view—these maps provide valuable insights into how conflicts are resolved, decisions are made, and objectives are achieved within the focused context.
Using social network mapping tools and creating effective social network diagrams or social networking charts enables researchers to untangle complex relationships and surface critical dynamics. This makes social network mapping a vital method in user research for understanding social influence and communication flows.
How to Create and Analyse a Social Network Map?
A social network consists of multiple nodes (individuals or actors) and ties (the connections between them). Creating a social network map involves visually representing these nodes as points or dots and ties as lines, helping to illustrate the structure of relationships within the network. The shape, size, and number of nodes and ties provide insights into how connections are formed and maintained. For example, an actor in a smaller network with fewer ties typically has less influence than someone embedded in a larger, more connected network. Similarly, an open network facilitates better information dissemination compared to a closed network.
The influence of a node depends on its connectivity within one or multiple networks, making centrality and degree important aspects in social network mapping. Moreover, accurately representing the nature of relationships between nodes enhances analysis, for instance, using plus signs for positive ties and minus signs for negative ones. When the overall product of ties in a network is positive, the network is considered balanced, indicating stable positive relationships. Conversely, a network with a negative product signifies potential instability, as negative connections can influence shifts in other relationships over time.
Researchers often apply social network theory to analyse families, organizations, and communities, and increasingly in digital contexts where online interactions connect users worldwide.
Stanley Milgram’s experiment and ‘Six degrees of separation’
In 1967, psychologist Stanley Milgram conducted a groundbreaking small-world experiment that became foundational to social network mapping in user research. In this study, participants were asked to pass a message through acquaintances to reach a specific target. The surprising result revealed that the average number of intermediaries or nodes required for the message to reach its target did not exceed six. This phenomenon led to the popular concept known as the “Six Degrees of Separation.”
Advantages of Social Network Mapping
1. Gather Information
2. Diverse Applications
Whether for companies, individuals, or countries, social network maps help in understanding competition, supporting product launches, driving successful campaigns, and facilitating user acceptance, both within organizations and online through influencers.
3. Predictive Insights
Analysing the balanced or unbalanced nature of social networks through social network diagrams allows researchers to predict the likely success of strategies or campaigns. By evaluating the positive or negative signs of ties between nodes, one can identify the best routes to improve the chances of achieving desired outcomes.
Challenges of Social Network Mapping
1. Questionable Authenticity in Unbalanced Networks
Data gathered from actors or nodes in unbalanced networks may include unreliable or biased information. Researchers sometimes need psychological expertise to discern authentic data from gossip or noise, depending on the study’s focus.
2. Complexity
Social network mapping can be intricate and challenging to analyse, often requiring experienced researchers and specialized social network mapping tools to produce meaningful social network diagrams and actionable insights.