Network data

Network data refers to information that describes relationships and interactions between entities, which can be represented using the concepts of graph theory. A graph (in this context) is a mathematical structure consisting of vertices (also called nodes) and lines that connect pairs of these vertices. A vertex (or node) is the smallest unit in a network. In social network analysis, a vertex often represents an actor, such as a person, organization, or country. A line is a connection between two vertices, representing a relationship. There are two main types of lines: edges and arcs. An edge is an undirected line, meaning it connects two vertices with no specific direction. This is used to represent mutual relationships, like a family tie or a shared resource. In contrast, an arc is a directed line that has a sender and a receiver, making it useful for showing one-way choices or influences—for example, when one person selects another in a sociometric test. Other important line types include loops (a vertex connected to itself), bidirectional arcs (two arcs in opposite directions between the same two vertices), and multiple edges/arcs, where several lines exist between the same pair of nodes. A network is more than just a graph. It includes additional data such as labels (names) of the vertices, their coordinates, and the weights of the connections. These extra elements turn a basic graph into a meaningful network that reflects real-world structures like departments, warehouses, or social groups. In practical applications, such as the example of a company’s organizational structure, departments and warehouses can be represented as vertices, while their logistic or communication links are represented as directed, weighted arcs. These values help quantify the intensity or frequency of interaction between entities. Understanding network data through graph theory allows for clear modeling of complex systems and is widely used in fields such as sociology, computer science, logistics, and organizational analysis.

Network data describes connections between entities such as people, organizations, or places. These connections can be analyzed using graph theory, where the main elements are:

• Node  – represents an actor in the network, like a person or department.

• Relationship  – a connection between two nodes.

• Arc  – a directed relationship, showing one-way interaction (e.g., A → B).

• Edge  – an undirected relationship, indicating mutual connection.

• Multiple lines  – more than one relationship between the same two nodes, often with different meanings or weights.

This visual summary helps explain how real-world interactions can be modeled and analyzed as a network.