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Social network

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A social network is a theoretical construct used to study relationships. It focuses on social actors, such as individuals or organizations. These actors are linked by networks of dyadic ties. A dyadic tie is a relationship between two people. These ties represent the convergence of various social contacts. This approach is inherently relational in its nature. Instead of studying the properties of a single unit, researchers study the relations between units. This helps scientists understand the structure of whole social entities. It also allows them to explain the patterns observed within these structures.

Diagram of a social network
Diagram of a social network

Social network analysis involves identifying both local and global patterns. It can locate influential entities within a specific system. Researchers use these methods to examine the dynamics of different networks. For example, they study how misinformation spreads on social media platforms. They also analyze the influence of key figures in various networks. This field is highly interdisciplinary. It emerged from social psychology, sociology, statistics, and graph theory. It has now grown into a major part of network science. This field examines complex networks to see how they function as a whole.

Researchers analyze networks at three general levels. These levels are the micro-level, the meso-level, and the macro-level. The micro-level is the smallest scale of analysis. It often begins with a single individual, known as an actor or an ego. Within this level, scientists study dyads, which are relationships between two people. They also study triads, which are groups of three individuals. A triad is important for studying balance and transitivity. For example, Fritz Heider’s balance theory uses triads to explain social dynamics. A rivalrous love triangle is an example of an unbalanced triad.

Moreno Sociogram 2nd Grade
Moreno Sociogram 2nd Grade

Researchers also look at subsets like cliques, which are cohesive subgroups.

The history of this field began with several important thinkers. In the late 1890s, Émile Durkheim and Ferdinand Tönnies shared early ideas. Tönnies described two types of social groups. He called personal, direct ties Gemeinschaft, which means community. He called impersonal, formal links Gesellschaft, which means society. At the turn of the twentieth century, Georg Simmel studied network size. He examined how the size of a network affects human interaction. In the 1930s, Jacob Moreno developed the first sociograms. These were visual tools used to study interpersonal relationships.

Network self-organization stages
Network self-organization stages

Many different academic paths eventually merged into one field. In the 1930s, anthropologists like Bronislaw Malinowski and Claude Lévi-Strauss studied social structures. At the same time, Talcott Parsons worked in sociology to establish a relational approach. By the 1970s, scholars began combining these different traditions. Harrison White and his students at Harvard University were central to this movement. During this time, Stanley Milgram developed his famous thesis on the "six degrees of separation." This idea explores how people are connected through chains of acquaintances.

Barabasi Albert model
Barabasi Albert model

Modern developments have changed how we view digital connections. In the late 1990s, new models emerged to study online social networks. Researchers like Duncan J. Watts and Albert-László Barabási used new data. They studied "digital traces" left by face-to-face interactions. These researchers applied mathematical models to understand complex systems. This work helped bridge the gap between sociology and physics. It allowed for the study of large-scale patterns in a digital world.

Scale-free network sample
Scale-free network sample

These models help explain how networks organize themselves.

Social networks are often self-organizing and emergent. This means a global pattern appears from local interactions. As a network grows in size, these patterns become more apparent. However, analyzing every relationship in the world is not feasible. Limits in computing power and ethics prevent global-scale analysis. Researchers must choose a scale that fits their specific question. They might focus on centrality, which is the importance of a node.

Social Network Diagram (large)
Social Network Diagram (large)

This helps them understand the influence of specific parts. By studying these connections, we gain insight into the complex systems of our world.

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🖼️ Images & Media (7)
File:Barabasi Albert model.gif
Barabasi Albert model.gif
File:Moreno Sociogram 2nd Grade.svg
Moreno Sociogram 2nd Grade.svg
File:Network self-organization stages.png
Network self-organization stages.png
File:Social Network Diagram (large).svg
Social Network Diagram (large).svg
File:Social Red.jpg
Social Red.jpg
File:Scale-free network sample.svg
Scale-free network sample.svg
File:Diagram of a social network.jpg
Diagram of a social network.jpg
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