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Journal : The Indonesian Journal of Computer Science Research

Sentimen Analis Thread Investasi Pada Twitter Menggunakan Naïve Bayes Hartatik Hartatik
The Indonesian Journal of Computer Science Research Vol. 1 No. 1 (2021): January
Publisher : Hemispheres Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (448.014 KB) | DOI: 10.59095/ijcsr.v1i1.13

Abstract

Social media is one of the market shares that allows people to consume news or promotions from an investment service because the source data is abundant and is updated every second on the internet. Social media is vulnerable to containing news or information on an investment platform and other forms of investment that are illegal or called fraudulent investments, so to overcome this, an Investment Thread Analyst Sentiment on Twitter is needed. The method used to evaluate investment threads to obtain positive and negative feedback is nave Bayes. The research results received a precision score of 0.69, recall of 0.70, f1-score (f-measure) of 0.74, and accuracy of 0.7.