00000ctmaa22000003a 4500 UP-1685675941123958233 Buklod 20180817121919.0 aa rb |||1 u| ta 180817s xx d r |||| u| (iLib)UPTAC-00019010353 UPVTC eng LG 993.5 2017 C66 L34 Lagarto, Jareinne Jae L. Tweetify authorship identification on different persona groups using Hybrid Extreme Rotation Forest. Jareinne Jae L. Lagarto [4], 66 leaves illustrations. Undergraduate thesis (B.S. Computer Science) -- University of the Philippines, Tacloban. Authorship Attribution is the process of determining the writer of a document. While many researches have been conducted to determine a writer of long texts such as blogs and emails, short text Authorship Attribution has proven to be quite the challenge. This study presents an author attribution system that extracts features from different Philippine social media users and uses the Hybrid Extreme Rotation Forest (HERF) for the author classification model. The results of our experiments show that using the Hybrid Extreme Rotation Forest along with the different feature extraction techniques is effective in classifying the author of short text such as tweets from Twitter. FI UP UPTAC UPTAC LG 993.5 2017 C66 L34 Thesis