Since lack of time & busy in emergencies…. This is one of my unpublished articles I wrote in 2013. Some datahulk fans might like it. Should be read along with the new paper The Computational Challenge of Amartya Sen’s Social Choice Theory in Formal Philosophy https://www.researchgate.net/publication/339022300_The_Computational_Challenge_of_Amartya_Sen's_Social_Choice_Theory_in_Formal_Philosophy
(Blockchain missing from the paper which could have been a huge help)
Coming back to 2013 -
Predicting virality social media messages through NavierStokes (node2vec & confusion2Vec we’re not algorithms yet)… Also I am not setting up a game & Nash entropy between stubborn & non-stubborn players…before Facebook’s work on mechanism design for social good….. not any GANs.. No CurvGAN, No TopologyGAN also not using Ricci flow ( https://youtu.be/z_pjsJisdHQ )but Gibb’s energy & Navier Stokes in information geometry in a very very simple English….
Assume that information flows through the social networks. Information flow through social networks can be measured in terms of Gibbs entropy. When it comes to complex networks, information flow can be measured in terms of nash entropy or Perelman entropy. Now, is there connection between Shannon entropy and navier stokes equation?
About Navier Stokes
Waves follow our boat as we meander across the lake, and turbulent air currents follow our flight in a modern jet. Mathematicians and physicists believe that an explanation for and the prediction of both the breeze and the turbulence can be found through an understanding of solutions to the Navier-Stokes equations. Although these equations were written down in the 19th Century, our understanding of them remains minimal. The challenge is to make substantial progress toward a mathematical theory which will unlock the secrets hidden in the Navier-Stokes equations.
Turbulence in social networks – Whenever a social media campaign is run, the turbulence and push of the information is created in specific nodes of social networks and information flows through the pipes connecting different nodes. Can we identify which nodes the information will flow through and calculate the turbulence which we call as social buzz created by the campaign? It is highly possible.
1. The way fluid changes its properties get changed when pressure and temperature is changed in the fluid system. Fluid can be lost to some extend during the curvature of the flow etc.
2. Similar way, when information flow is pushed through different nodes of the social media or social network, information fluid changes its properties. The information message can miss few bits of information while getting forwarded.
Combining all three formulas, depending on your initial node, we can calculate through which nodes information will flow at what viscosity and velocity and identify whether your post/message on facebook or twitter will go viral or not.
We can also calculate which nodes (nano influencers) are supposed to be tapped in order to make your post viral and identify natural pockets where information can be fed from where there will be free fluid flow and your message can reach millions.
This exercise is very specific to the node from which you are sending the information in social network, what is your message about and the surrounding nodes/social media profiles to your node or social media profile. Also how distant are the natural pockets/nodes which can distribute your information effectively and the pressure required from social media campaign to push your message or information flow to these nodes.
References:
