  Text mining can be applied to many fields. One of the application is using
text mining in digital newspaper to do politic sentiment analysis. In this
paper sentiment analysis is applied to get information from digital news
articles about its positive or negative sentiment regarding particular
politician. This paper suggests a simple model to analyze digital newspaper
sentiment polarity using naive Bayes classifier method. The model uses a set of
initial data to begin with which will be updated when new information appears.
The model showed promising result when tested and can be implemented to some
other sentiment analysis problems.
