Motivation:
The new IT socio-economic ecosystem is based on the advancement of information technologies that enabled real time connection between different peers(households & investors), firms(investors & advertisers), governments(financial regulation and supervision) to trade their socio-economic assets(creations, products and services) using Internet capabilities, i.e. this information technology is used to match directly buyer peers and seller peers that are forming a network on an on-line platform.
Known IT socio-economic ecosystem sites are Youtube for online creator videos, and online marketplace lending, such as Lending Club, in the financial services sector.
On-line contractual arrangements are created to mitigated the existing conflicts of interests between the on-line platform and its peers. New form of contracts are designed specifically for this IT socio-economic ecosystem platform to foster incentives for the contracting parties to exploit the anticipated gains from their on line collaborations.
- A creator can become part of YouTube’s Partner Program which is the adequate way to make money on YouTube. The Partner Program has many benefits, the most important for the creator is monetization.
- Or a creator can become part of a Multi-Channel Networks (“MCNs”) which are third-party service providers that affiliate with multiple YouTube channels to offer services that may include audience development, content programming, creator collaborations, digital rights management and to leverage the monetization.
- Both ways are presenting advantage of higher quality video, branded channel options, and insight analytics to help creator learn about their audience and increase or leverage their viewer-ship for an adequate monetization.
- The creator's anticipated gains from any contract is to have substantial views and more opportunities for continuously monetization.
- Online Marketplace Lending platform is a kind of IT socio-economic ecosystem that facilitates the direct matching of borrowers to lenders(investors) through online loan auctions.
- The online marketplace lending are designing credit contracts that are not necessary combining the
sharing of risk and efficient decision aimed at protecting the lender and encouraging sound decisions by borrowers as the loans are unsecured.
Platform's Performance Modeling
In spite of the fact that; the economic activity takes place "continuously" in an IT socio-economic ecosystem platform.
A peer populating the online platform is only socially or economically connected to the platform during a consecutive finite number of periods and are not necessarily regularly connected.
Globally, the peers populating the online platform are forming an overlapping or staggered network. Staggered implies any portion of the peers with similar social or economical characteristic to interact with the platform.
My main motivation, this property of staggered connexions is a central feature in mathematical modeling of online platform performance dynamics. My theoretical mathematical formulations and statistical analysis approaches to this micro-interaction foundations are proved essential to build a macroscopic scales to estimate the online platform performance dynamics.
Numerics & Analytics of IT socio-economic ecosystem platform
The data type used for the result of a calculation depends on the type of the IT socio-economic ecosystem platform, its business model and the associated operations performed on the online platform.
YouTube and Creator's Anticipated Gains
- YouTube Differential Analytics::
- YouTube Most Popular Videos & Learning Engagement With Bursting Velocity.
- Coupling Time Variable Bursting Traffic Intensity & Policy Effect Functions: Nonlinear Phenomena and Properties.
Online Marketplace Lending Analysis
- Lending Club Datasets.
Deep Discrepancy Microscope:
- Image Content Analytics Using Discrepancy Learning Process .
- Modern Pathology & Discrepancy Image Using Discrepancy Learning Process .
- Imaging Flow Cytometry Using Discrepancy Learning Process .
- Predicting Lineage Progression of Stem Cells Combining Nanoscopy Epi-Mark Imaging & Deep Discrepancy Learning Process .
- Retinal Optical Coherence Tomography Imaging Using Deep Discrepancy Learning Process (DDLP) .
Cohort Formation, Accuracy & Reliability of Precision Medicine Projects:
Empirical Assessment of Public Socio-Economical Data Using Mathematical Machine Learning:
Author scientific profile:
Statistics and Applied Mathematics for Data Analytics, Identify opportunities to apply Mathematical Statistics, Numerical Methods, Machine Learning and Pattern Recognition to investigate and implement solutions to the field of Data Content Analytics. Data prediction via computational methods to predict from massive amounts of data (Big Data Content). These methods included clustering, regression, survival analysis, neural network, classification , ranking, deep discrepancy learning .