Penerapan Long Short Term Memory dalam Mengklasifikasi Jenis Ujaran Kebencian pada Tweet Bahasa Indonesia
Abstract
Tweets are messages posted to Twitter and contain photos, videos, links, and text. Twitter is a social media service that allows everyone to communicate and stay connected through the rapid and frequent exchange of messages. However, as many communities have sprung up, the user is getting more and more out of control while communicating on Twitter. One of them, more and more hate speech is being hurled either through retweets, or replies to each other in one of the threads belonging to a particular community. To minimise this impact, a classification is needed to find out whether the tweet contains hate speech or not before being uploaded to Twitter. Due to the rapid increase in the current data, it is necessary to review it with other methods to classify the data more deeply. Based on these problems, the method that can be used is Long Short Term Memory (LSTM). This study succeeded in providing predictions with different hyperparameter accuracy values for the LSTM application reaching 74%.
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