Machine learning and Lexicon based approach to Sentiment analysis using Twitter API
Description
Unlock the power of Twitter data with this in-depth course on connecting to and downloading tweets through the Twitter API. Whether you’re interested in analyzing social media trends or conducting sentiment analysis for research or business, this course will guide you every step of the way. You’ll start by learning how to access Twitter’s vast data through its API, downloading tweets that are relevant to your chosen topic.
Once you’ve gathered your data, I’ll show you how to clean and preprocess it, transforming raw tweets into structured data that’s ready for analysis. From there, we’ll dive into the fascinating world of sentiment analysis, exploring the two most commonly used approaches. The first is the Lexicon-based approach, where you’ll leverage pre-built lexicons to determine the sentiment of given text quickly and effectively. This method is great for those looking to get started with sentiment analysis without deep machine learning knowledge.
The second approach is more advanced, using Machine Learning to train a custom model on labeled data. Once your model is trained, you’ll apply it to new data, allowing it to predict sentiment with increasing accuracy. By the end of the course, you’ll have built a powerful script capable of analyzing the sentiment of hundreds or even thousands of tweets on any topic you choose. Whether you’re a beginner or looking to expand your data science toolkit, this course will equip you with practical skills and knowledge to perform sentiment analysis on real-world Twitter data.
What you’ll learn
- How to create twitter developer account and connect to twitter API
- Download Tweets, clean and store them in to Pandas DataFrame
- Learn about Tokenization, Lemmatization, Stemming and much more
- Perform Sentiment analysis with Vader and TextBlob lexicons
- Learn about Machine learning approach to Sentiment Analysis
- Build and test machine learning models
Who this course is for:
- Beginner Python developers curious about data science
- Anyone who is interested in data analysis
- People who wants to include sentiment analysis for their projects