Text classification is one of the most commonly used text mining tasks. In this discussion, download the following dataset (Twitter US Airline Sentiment). Then create a Jupyter notebook file, and you do the following: Describe the data Write Python code to load and clean the data from any unnecessary parts (you should decide what data pre-processing steps to apply). Write Python code to derive and estimate the sentiment associated with individual tweets Store the output as a data frame that contains the following columns: the tweet and the associated sentiment. Be sure to display the head of this data frame Be sure to include a clear explanation before each step you do in a markdown cell in the file Comment your source code and describe your code to someone who may be viewing it for the first time
Text classification is one of the most commonly used text mining tasks. In this discussion, download the following dataset (Twitter US Airline Sentiment). Then create a Jupyter notebook file, and you do the following:
Describe the data
Write Python code to load and clean the data from any unnecessary parts (you should decide what data pre-processing steps to apply).
Write Python code to derive and estimate the sentiment associated with individual tweets
Store the output as a data frame that contains the following columns: the tweet and the associated sentiment. Be sure to display the head of this data frame
Be sure to include a clear explanation before each step you do in a markdown cell in the file
Comment your source code and describe your code to someone who may be viewing it for the first time
Trending now
This is a popular solution!
Step by step
Solved in 5 steps with 3 images
