Abstract:
Social media now shapes public opinion about governments and businesses. Thus, an effective method is needed to understand social media posts’ sentiment. We examined political sentiments on Facebook.
Keywords dominate political postings. First, we created a dictionary of unique words from political or non-political posts or comments and trained it using Naive Bayes algorithm.
We extracted each word of a new post or comment and matched them with dictionary words to classify its sentiment.
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