Networks are made up of entities, connections and signals which can be represented mathematically using graphs and tables.
In social networks, entities are the people who make up the network, connections are the paths through which information is transferred and signals are the actual messages or bits of information being shared.
Broken down and represented in this way, a social network appears to be a very simplistic process, however, understanding the relationship between each of these components reveals the various levels of complexity which makes up a social network.
How a network is connected determines what and how information moves around the network. If the entities within a network are all closely related, the amount of new information will be limited, as each entity is sharing the information with each other. However, a network with external connections or ‘weak ties’, that are not closely related to one another will have a much bigger influx of new and fresh information.
The way information flows in a network also determines how well information is circulated. Information can travel one way or be reciprocal and can also be onward flowing. Each of these methods of transference determines the fluidity of information, as does the frequency and filtering of information and the level of influence an entity is seen to have within the network. We do not all have to be directly connected to access and share information – 2, 3, 4 degrees of separation can also allow access to the information of others without having to be directly connected.
Networks can prejudice how we think and the power/strength of a network is not always positive.
The effect of the recent Wall Street financial collapse on the international monetary market is the result of networks. If we consider banks to be the ‘entities’ in the network, who are all closely ‘connected’ and cash/money being the ‘signal’ or information, we can see that the poor home loan lending practices of some US banks have meant that home mortgages have not be repaid to return funds into monetary markets (one way flow). This ‘leak’ or drain of money (information) from US banks means less fluidity of funds between their international partners (all closely linked) – creating a domino effect on the reduction of cash reserves globally.
Having an understanding of the properties or components of your network can help you manage and influence the optimistic and disasteristic characteristics of the network. Knowing who makes up your network, their influence/power, how the information flows and is filtered will also allow you to better understand the what, when, who and how of new knowledge from a network.
In social networks, entities are the people who make up the network, connections are the paths through which information is transferred and signals are the actual messages or bits of information being shared.
Broken down and represented in this way, a social network appears to be a very simplistic process, however, understanding the relationship between each of these components reveals the various levels of complexity which makes up a social network.
How a network is connected determines what and how information moves around the network. If the entities within a network are all closely related, the amount of new information will be limited, as each entity is sharing the information with each other. However, a network with external connections or ‘weak ties’, that are not closely related to one another will have a much bigger influx of new and fresh information.
The way information flows in a network also determines how well information is circulated. Information can travel one way or be reciprocal and can also be onward flowing. Each of these methods of transference determines the fluidity of information, as does the frequency and filtering of information and the level of influence an entity is seen to have within the network. We do not all have to be directly connected to access and share information – 2, 3, 4 degrees of separation can also allow access to the information of others without having to be directly connected.
Networks can prejudice how we think and the power/strength of a network is not always positive.
The effect of the recent Wall Street financial collapse on the international monetary market is the result of networks. If we consider banks to be the ‘entities’ in the network, who are all closely ‘connected’ and cash/money being the ‘signal’ or information, we can see that the poor home loan lending practices of some US banks have meant that home mortgages have not be repaid to return funds into monetary markets (one way flow). This ‘leak’ or drain of money (information) from US banks means less fluidity of funds between their international partners (all closely linked) – creating a domino effect on the reduction of cash reserves globally.
Having an understanding of the properties or components of your network can help you manage and influence the optimistic and disasteristic characteristics of the network. Knowing who makes up your network, their influence/power, how the information flows and is filtered will also allow you to better understand the what, when, who and how of new knowledge from a network.
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