A STUDY ON THE SENTIMENT ANALYSIS (POSITIVE, NEGATIVE) OF WORDS APPEARING IN KYRGYZ NEWS BY APPLYING THE DEEP LEARNING-BASED NLP (NATURAL LANGUAGE PROCESSING) TECHNIQUES FOR STUDENTS PRACTICE

Abstract

This study is theoretical on the sentiment analysis field of deep learning-based natural language processing, which is the world's advanced technology, namely data collection and preprocessing stage, tokenizing stage, Sentiment Dictionary construction stage, positive and negative word extraction stage through sentiment analysis, deep learning introduces major contents and related technologies such as model configuration, execution stage, and data visualization stage. In addition, speech processing technology performed in the data collection stage, STT (Speech to Text) and TTS (Text to Speech) technology will be introduced. In this study, a program was written using various open sources (libraries) including ’keras’ 2.0 version used in the deep learning natural language processing field of the python language base. This study is executed to help students who are studying deep learning natural language processing.