Analisis Sentimen Mengenai Gangguan Bipolar Pada Twitter Menggunakan Algoritma Naïve Bayes

Bipolar disorder is one of the world's most common mental health disorders. To find out public sentiment regarding bipolar disorder, analysis carried through social media to analyze positive or negative sentiments with aim maintaining towards problem disorder. Twitter a that often used exchange information, discuss, and even express emotions. The emotions users can be called sentiment. Sentiment also see opinions tendencies an opinion. Opinion in form sentiments. data this study uses keyword. There are 2177 tweets were successfully obtained crawling process using API key access from developers, after which will processed preprocessing. comparison presentations 70.92% expressing opinion 29.08% favorable results nave Bayes algorithm accuracy value 92.110092%.