[GET] Performing Sentiment Analysis on Customer Reviews and Tweets

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Performing Sentiment Analysis on Customer Reviews and Tweets
Learn how to perform sentiment analysis and emotion detection using TextBlob, NLTK, BERT, VADER, NRCLex, MultinomialNB
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864 students
3 hours on-demand video
3 downloadable resources

Description
Welcome to Performing Sentiment Analysis on Customer Reviews and Tweets course. This is a comprehensive project based course where you will learn step by step on how to conduct sentiment analysis and emotional detection on customer review and twitter post datasets using TextBlob, Natural Language Toolkit, and BERT models. This course is a perfect combination between theory and hands-on application, providing you with practical skills to extract valuable insights from textual data. This course will be mainly focusing on two major objectives, the first one is data analysis where you will explore the customer review and twitter post datasets from multiple perspectives, meanwhile the second objective is sentiment analysis where you will learn to detect emotions and bias from customer reviews and twitter posts. In the introduction session, you will learn the basic fundamentals of sentiment analysis, such as getting to know its practical applications and models that will be used in our projects. Then, in the next session, we are going to have a case study where you will learn how sentiment analysis actually works. We are going to use customer reviews dataset to perform feature extraction and make predictions if a review is more likely to be positive, negative, or neutral. Afterward, you will also learn about several factors that contribute to bias in customer reviews, for examples like algorithmic amplification, emotional bias, and financial incentives. After learning all necessary knowledge about sentiment analysis, we will begin the project. Firstly you will be guided step by step on how to set up Google Colab IDE. In addition to that, you will also learn how to find and download customer reviews and twitter post dataset from Kaggle. Once everything is all set, we will enter the main section of the course which is the project section. The project will consist of two main parts, in the first part, you will learn step by step on how to perform sentiment analysis on customer reviews dataset, you will extensively learn how to make accurate predictions whether the review indicates customer’s satisfaction or dissatisfaction based on the training data. Meanwhile, in the second part you will be guided step by step on how to perform sentiment analysis on twitter posts dataset, specifically you will analyse the emotional aspect of the tweets using Natural Language Toolkit.

https://www.udemy.com/course/performing-sentiment-analysis-on-customer-reviews-tweets/?couponCode=9434AD44056126B8AB26

Enjoy!