What Small world village clusters can teach us on randomness and order in social networks

small world village
Modern small world village clusters are the way forward. They not only provide communication technology but also urban and social infrastructure for development. They are well connected, thriving and sustaining. The above picture is from Nazilzang, Pixabay. Image credit: Pixabay

During my recent studies on understanding social network analysis, by attention fell on a book titled ‘Social networks – An Introduction’ by Jeroen Bruggemen.  I wanted to present a comprehensive post on social network analysis, which I will do soon. The chapter on ‘Small world’ was fascinating.

The example depiction of a farmer’s access to information in an African village was quite interesting. It showed how the ‘Small world’ phenomenon can change their world.

We have known that some of the African indigenous village people have built their hut settlements spread over large tracts of grasslands over the open Savanah. They do this in a circular fashion across the open grasslands. The people within the village often travel long distances to reach their neighbors and have no means of transportation or communication. A small world they are but not so anymore.

I attempted to use a similar example for a cluster of villages in India and consciously avoided the math part of it.

Below is a brief note on  small world network and how they help us understand randomness and order in social networks.

The Wikipedia defines a small world network as a mathematical graph. The connecting dots or nodes are all neighbors to each other. Every other node can reach every node by a small number of hops or steps.

If ‘L ‘is the distance between two randomly selected nodes then the number of hops is directly proportional to the logarithm of the number of nodes ‘N’ in the network.

L  α log N

For example, if the number of nodes is 1000. Then the logarithm of 1000 is 10x10x10 = 10 3. Logarithm of 1000 (to the base 10) is 3

This results in a small world network where strange bedfellows connect to each other through a short chain of acquaintances.

Investigating social relationships in a social network is a difficult subject. It is not something that we can put it in a microscope and examine it. Thanks to social media analysis tools, this is now possible.

We only know a tiny fraction of the whole world. The world is huge and as such, the density is low. Research says that we all know each other through 6 or 7 orders of magnitude. To put it another way, we are all clustered together as one big family all related to each other in a highly structured fashion. This family could be a family of friends or relatives and we all know each other through it. In effect, we are one step away from each other and so are others.

It is difficult for us to fathom and understand that how swathes of people are all related to each other. Thinking in those lines, we are bounded by our rational thoughts and choices. Our choices are limited by the extent of the information flow within the network and to ourselves. Therefore, we cannot optimize our choices.

It would be no harm, if I say that that there is a considerable bias in our perception and cognition of circumstances and situations around us emboldened by this network. We are all separated by ‘Six degrees of separation’. We are living in a ‘small world’.

Have you read ?

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Frigyes Karinthy a fictional writer first noticed the phenomenon of small world in 1929 and other independent researchers later popularized the topic in the 1960s’. Duncan Watts solved the concept of average small distance in 1998 who apparently has interdisciplinary co-ordination with other researchers from various disciplines.

As years went by there was lot of insight that was drawn by researchers and crucial among them was the way the world looked at social networks. They said social networks need order and a touch of randomness as well.

Social networks are neither ordered nor at random. In fact, in my perspective they happen at the edge of chaos- a state where it is neither too loose nor too rigid for a system to thrive and sustain. We can say that Social networks are ordered with a tinge of randomness in the air. Interesting!

For example, we as people do not choose others (friends or relatives) at random, do we?

Similarly, others do not. If we were a family, it is structured and ordered like a hierarchical family tree and then we are free to seek random interactions within it.

Similarly, we choose our friends based on sympathy for each other. Even though we might say that some of us might have encountered each other at random in the first instance but later on sympathy and order emerges isn’t it.

People join and become employees of big corporations but then their internal relationships are highly ordered. Like the relationship of the manager with his direct reports. There are social groups within large corporations, where employees can form social relationships at random.

An example: Remote village clusters in India

To illustrate this with an example, we can look at remote cluster villages in India. A village council called ‘Gram panchayats’, an age old institution in India headed by a Sarpanch (an elected head) sorts out local governance issues. There are about 250,000 gram panchayats in India.

If a farmer living in one of the villages has no access to modern information network nor any means to commute to other villages, then his world would be limited and restricted. He or she would not have access to, let us say – newer farming methods or social welfare schemes. So would be his other ignorant fellow village members.

Without access to modern information flow and means of transportation, valuable information would take longer to pass from one village to another as it passes consecutively from one village council to another.

There is information attrition as well. Sometimes out of attrition, information might not reach the final recipient and it might die along the way. It might as well be a case of ‘Chinese whispers’.

If on the other hand, if the farmers had the means to reach other villages, then information would reach much faster and easily as well. In fact, the people in other village clusters more often than not are their own kith and kin. Information passes two ways from one side to other side. Everyone stays informed.

Many of the village based movies in the 80’s and the 90’s in India were reminiscent of the frequent village feuds that had happened because the information was not passed on time among the village elders and there was information attrition as well in the network. An instance of free flowing randomness of a friendly interaction over connective networks can change things for the better, forever.

Now all the 250,000 village Gram panchayats are digital enabled with giga bit –broadband under the Bharatnet and Digital India initiative. This initiative makes sure that everyone is informed and stays informed.

We are all living in a small world. The small world phenomenon presents us an opportunity to understand the workings of the society and various communities that are structured within it.

As Miller points out ‘We are all bound together by a tightly knit social fabric’. In essence, we can say that the world is not made up many networks but one huge global network with small clusters.




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Ramkumar Yaragarla

I am 43 years old. Founder, Loving dad and Husband. Worked as an IT Business analyst and program manager in several Fortune 100 companies.Alumnus at the University of Warwick, UK. I love the WWW and write on Social aspects of information, Social collaboration, Digital Sociology, Digital Humanities and Work life balance. I enjoy playing on the beach with my 9 year old daughter. I am open to your suggestions and comments.
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