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Twitter Sentiment Analysis Tutorial in Python
Created by a Stanford alumni team, this sentiment analysis tutorial uses Python and Twitter API to teach you how to build your own sentiment analyzer.
Sentiment Analysis or Opinion Mining is a field of NLP that is concerned with deriving subjective information about a person's attitude towards a topic, whether it is positive, negative, or neutral. It is concerned with extracting information about individual likes, dislikes, and emotions that are attached to a product. Social media sentiment analysis is a brilliant source to gain insights about market preferences, and numerous companies develop their marketing strategies based on these inferences. This Twitter sentiment analysis tutorial in Python will give you the skills to create your own sentiment analysis measurement system.
What will you gain from this sentiment analysis tutorial?
- Understand the importance of Sentiment Analysis Systems
- Know about the theories underlying sentiment analysis, and its relation to binary classification
- Learn how to develop and utilize a sentiment analysis measurement system in Python
- Diagnose use-cases for sentiment analysis
Prerequisites and Target Audience
Having knowledge of undergraduate level Mathematics will make understanding this course simple. However, it is not a prerequisite. If you would like to run the source code, you will require working knowledge of Python.