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Tweet Classification for Political Sentiment Analysis. Micol Marchetti-Bowick. Problem Overview. Tweet Sentiment. Sentiment Classifier. a utomatically labeled tweet sentiment using emoticons t rained a Naïve Bayes classifier on 2M tweets u sed both unigram and bigram features - PowerPoint PPT Presentation
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Tweet Classification for Political Sentiment Analysis
Micol Marchetti-Bowick
Problem Overview
Tweet Sentiment
Sentiment Classifier• automatically labeled tweet
sentiment using emoticons
• trained a Naïve Bayes classifier on 2M tweets
• used both unigram and bigram features
• 79% test accuracy on 0.5M labeled tweets
Tweet Political Relevance
Political Classifier• automatically labeled tweet
political relevance using key terms
• trained a Naïve Bayes classifier on 2M tweets
• used both unigram and bigram features
• 96% test accuracy on 0.5M labeled tweets
Obama Sentiment Analysiscorrelation coefficient = 0.188 (approval), 0.399 (disapproval)
General Political Sentiment Analysiscorrelation coefficient = 0.743 (approval), 0.737 (disapproval)
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