Abstract

As social media nowadays becoming more popular it is also turning to be more advance., for example, the review of new websites and articles has a regular decent commitment, and the estimation examination by means of online papers has become one renowned examination region. Investigation of sentence orientation is the purpose to find the use the valuable orientation information. This paper analyses Facebook comments and posts using Term semantic value focusing on NLP. Firstly, this paper consists of sentiment analysis. later on, we will work on a machine learning algorithm. In our Proposed work we create the database in two ways first is by single comment and second is by uploading multiple review at one time. First approach is length and also time consuming and second approach is shortcut and works faster. Applying feature extraction in each comments and then converting it to ASCII code which turns comments as secure. After that we will categories these comments in three techniques i.e. positive, negative and neutral. The classification technique splits the data in two parts training and testing which classifies the percentage of each category.

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