Twitter sentiment classification for measuring public health concerns

Keyphrases

• Public Health Risk 100%
• Twitter Sentiment Classification 100%
• Tweets 100%
• Machine Learning Models 75%
• Public Concern 75%
• Training Data 50%
• Public Health 25%
• Health Problems 25%
• Automatically Generate 25%
• Different Datasets 25%
• Surveillance System 25%
• Communicable Diseases 25%
• Nave Bayes Classifier 25%
• Mental Health 25%
• Two-step Method 25%
• Sentiment Classification 25%
• Two-sub-step 25%
• Twitter Posts 25%
• Disjoint Datasets 25%
• Public Health Officials 25%
• Classification Approach 25%
• Health Domain 25%

Computer Science

• Machine Learning 100%
• Twitter 100%
• Sentiment Classification 100%
• Training Data 66%
• Bayes Classifier 33%
• Public Health Official 33%
• classification approach 33%
• Twitter Message 33%
• Nave Bayes 33%

Mathematics

• Training Data 100%
• Two-Step Method 50%
• Nave Bayes 50%
• Keeping Track 50%