Lab 10 Use K-Means Clustering to Identify #Twitter Topics in #RapidMiner
Channel: LBSocial
Date: 2020-10-29

Objectives:
• To learn how to cluster Twitter data with the K-Means model.

Data: 
• Optional: collect about 1,000 tweets in RapidMiner
• Or use the tweets provided on Canvas

Steps:

1. Optional: collect 1,000 tweets in RapidMiner, define your keyword, export the collected tweets into an Excel file.
2. Import the Excel file, clean and tokenize the tweets.
3. Use K-Mean to cluster the Twitter texts into several groups, define your k.
4. Visualize the clusters with the Cluster Model Visualizer.
5. Aggregate the result to calculate the average weight (TF-IDF score) of all words in each cluster.
6. Create word clouds for each cluster.



More about Machine Learning: https://www.youtube.com/playlist?list=PLHutrxqbP1Bx-zZxtex-EgwMFsjjjwYGO