Systems biology is studying biology as a holistic system which is in strict contrast to the traditional/orthodox way of studying biology, which is from a reductionist’s approach. Reductionists study systems by reducing them into subunits… like a poet said about studying sub-atmic particles ..”akin to breaking watches to see how they are working”. Systems biology also led to the ‘invention’ of a sister field called Synthetic biology. There is much hype about Synthetic Biology these days. When we started studying systems/emergent properties of biological systems, we also identified moduarities of sub-systems. By modularity I mean the ability to plug and play. Components that can be taken out of a cell and attached into another to give the recipient cell some properties of a donor cell.
What is striking is that this science of systems is not only limited to biology. It is a charachterstic of most, if not all, complex systems. And we, socially, are just that. A complex organism. With the advent of Big Data and social networking the study of such an organism has become feasible. And what I saw on FB the other day, made me think about Einstein’s quote, “I don;t think about the future as it comes soon enough”.
Recently, There has been much discussion about FB’s data science unit’s valentines day graph[1]. This graph predicts that when one falls in love there is a marked increase in exchange of messages and posts between to prospective lover’s timelines. This may not be 100% predictive right now but with more variables more concrete models can be made.
Another thing I read about was a mini study by Computer Scientists of University of Maryland [2] and it showed that twitter groups can be categorized into at least 6 kinds of groups with unique graphical contours. These six groups are namely;
Polarized Crowds that often form around political topics and communicate very little with those holding opposing viewpoints.
Tight Crowds that share spaces of learning and passion.
Brand Clusters that form around products and celebrities.
Community Clusters created around global news, with popular topics developing multiple smaller groups.
Broadcast Network structures created by people re-tweeting commentary from pundits and breaking news.
Support Network/customer service conversations that revolve around a singular source.
For those who are close to systems Science, might have gotten the hint that these are actually, network motifs. “Network Motif” was the term, first used by Dr. Uri Alon in his papers that revealed oft repeating patterns in graphs of clusters in a biological networks. Each of these motifs, defined by a particular pattern of interactions between vertices, may reflect a framework in which particular functions are achieved efficiently. Motifs are important because they may reflect functional properties. They provide a deep insight into the network’s functional abilities. Hence, the discovery of the clusters in twitterverses are the first ever report of observing network motifs in social networks.
Now suppose if these network motifs are modular and one can pl
ug and play these motifs with other motifs to produce desired output which may or may not exist in naturally occuring social networks, just like in synthetic biology. What would be implications of it. Like all great scientific discoveries there are both good and bad implications.
Suppose a political party might want to reduce the oposition from public to its controversial reforms, all it will have to do will be to identify the interactome(the full network of opposers of its policies) and then insert appropriate network motifs to reduce the noise from the opposers. Or a political party can setup its unique network motifs as feedbacks working like thermostats to people’s true needs and wants.
An advertisement company can use these instruments to make people more responsive to their adds.
the implications can be countless. To sum up we are entering into a new era, where big data and systems science is going to play a crucial role. Where not only prediction but a true fabrication of reality will become possible.
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