Understanding Sentiment Analysis in Natural Language Processing

Sentiment Analysis is a supervised Machine Learning technique used to determine if a chunk of text is positive, negative or neutral. In text analytics, natural

language processing (NLP) and machine learning (ML) techniques are combined to assign sentiment scores to topics, categories or entities within a phrase.

Sentiment analysis is a powerful tool that businesses can leverage to better understand the overall opinions of their customer, gain insights and make

data-driven decisions.

In this tutorial we will classify text articles using VADER on a dataset from CrowdFlower

Import Libraries

import pandas as pd import nltk from nltk.corpus import stopwords from nltk.probability import FreqDist from nltk.tokenize import sent_tokenize , RegexpTokenizer from nltk.sentiment.vader import SentimentIntensityAnalyzer nltk . download ( ' stopwords ' ) nltk . download ( ' vader_lexicon ' ) nltk .…