Sentiment Analysis with Spacy and Scikit Learn

[francis966]

Proposed title of article

Sentiment Analysis with Spacy

Introduction paragraph (2-3 paragraphs):

Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. This technique is used to determine whether data is positive, negative, or neutral. Sentiment analysis is often performed on textual data to help businesses monitor brand and product sentiment in customer feedback, and understand customer needs. This is very useful to many businesses since it helps them with marketing their business and knows how customers will react to their products. Sentiment analysis is extremely important because it allows businesses to understand the sentiment of their customers towards their brand. By automatically sorting the sentiment behind social media conversations, reviews, and more, businesses can make better and more informed decisions. Sentiment analysis models focus on polarity (positive, negative, neutral) but also on feelings and emotions (angry, happy, sad, etc), urgency (urgent, not urgent), and even intentions (interested v. not interested). In this tutorial, we will use Spacy in building our model. Spacy is a natural language library that enables sentiment analysis using advanced machine learning.

Key takeaways:

1 . What is sentiment analysis and different types of sentiment analysis.

2. Application areas of sentiment analysis.
3. Getting started with Spacy.
4. Building our pipeline using Spacy for sentiment analysis.
5. Building a model for sentiment analysis.

References:

Please list links to any published content/research that you intend to use to support/guide this article.

Templates to use as guides

• How To Guide Template
• Software Review Template
• Tutorial Template

[WanjaMIKE]

Good afternoon and thank you for submitting your topic suggestion. @francis966 Your topic form has been entered into our queue and should be reviewed (for approval) as soon as a content moderator is finished reviewing the ones in the queue before it.

[lalith1403]

Great topic 🚀 , make sure it matches the following:

• Adds value beyond what is in the official docs and what is covered in other blog sites.
• To avoid potential article closure, it should not overlap with existing EngEd articles or incoming topic suggestions.

Please reference any relevant EngEd articles in yours and build a unique project - Approved. @francis966

[francis966]

Hello @lalith1403, kindly check this topic suggestion I have made some minor adjustments.

[WanjaMIKE]

Closed #3631 via #3892