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25th February 2009

In most social media users tend to disseminate information in one form or the other. One user generates a piece of information that is then made available to other users within the original user’s network.
From here the information can either lay dormant, disappear or be transmitted to another network by other users. This can be applied to social media as a rule of thumb. In the case of transmission of information social media can be thought of as Complex Networks.

“Most social, biological, and technological networks display substantial non-trivial topological features, with patterns of connection between their elements that are neither purely regular nor purely random. Such features include a heavy tail in the degree distribution, a high clustering coefficient, assortativity or disassortativity among vertices, community structure, and hierarchical structure. In contrast, many of the mathematical models of networks that have been studied in the past, such as lattices and random graphs, do not show these features.” (LINK - Accessed 25th February 2009)

The focus in social media is the ‘patterns of connection between their elements that are neither purely regular nor purely random’ – in effect that is how a network in social media is produced. It has been concluded that the Internet and many of its features and modulations are in essence complex and small world networks.
What this article is interested in is how content or information passes through these networks and what effect this has on users?
 
 Conserved Spread and Non-Conserved Spreads in Complex Networks
Information or content in complex networks tends to spread via two methods:

1. Conserved spread and;
2.  Non-conserved spread.

In the conserved spread model the total amount of information that enters the network remains constant as it passes through. Imagine a network as a set of interconnected nodes. Each node represents a point or a user for instance if applied to social networks. As the information passes from node to the other it leaves nothing behind.
So the node or the users that was exposed to the information retains nothing of information after it has been transmitted to the next node or user. This model can mainly be applied to purely technological systems where the need to retain information is not needed. UDP transfers of data are a good analogy for a Conserved Spread.

In a Non-conserved Spread the information is deemed to be infinite which is certainly the case with social media networks that are in operation. Social Media depends on its users to constantly feed information into the network in order to keep it “alive”. Once the flow of information stops the social media network itself will cease
(This could be investigated further under “Life-Cycles of Social Media Networks”). 
In the non-conserved spread information that is received by a node or a users will continue to experience the content or information even as it is transmitted to another node or user. What is interesting about this model to social media networks is that the Non-Conserved Spread Model is extremely suitable for explaining the transmission of infectious diseases.

The point here is that information in social media networks like twitter behaves like infectious diseases and in such the information/content is thereby viral in its ability to spread throughout the network. In this way there is a similarity between Social Media Networks and other technological and biological networks.
There is another way in which Social Media Networks are related to viral diseases: the way in which its spread. Here I am going a bit out of my main knowledge and research area but; if one could overlay a time-lapse mapping of the spread of Twitter or Facebook with one of AIDS or Flu – one (I am sure) would see similarities in the way in which they spread. The similarity would be looking at how from an epicentre the spread would spiral out to surrounding regions – creating other epicentres which again would spread out and create other smaller epicentres.

Twitter’s epicentre would probably be West Coast USA where as AIDS would be Africa. (If anybody has done any research on this please feel free to email me on jrm@mechanosphere DOT com I would be extremely interested in this area)
The similarity between Social Media Networks and infectious diseases can be that Social Media Networks are not entirely technological or biological but a fusion of both. Social Media Networks needs to input in the form of information/content from users.
Without information it is just a digital platform. Social Media Networks have come into existence because of the technological space has been enabled but its life is the information which users contribute and transmit through its network. 

 

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