Confidence Score For Trained Sentiment Analyser Model
I was able to solve it myself after some further research. 
I will be briefly describing my approach here.
Cheers!

The idea is to find the confidence interval which was also same as finding the distance from the decision boundary / hyper-plane, in my case. 

If you are using the Scikit Learn API, there is a method called predict_proba() for several classification models like Logistic Regression, SVM, Random Forest, etc. If your classifier does not provide one, you can wrap it with the CalibratedClassifierCV which can be found in sklearn.calibration, then use the above method to calculate the distance from the decision boundary.

If you are looking for custom in-depth implementation, here are some papers / references that might help.


Ref - 1
Ref - 2