title: ÐÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ ÑÐµÐºÑÑÐ¾Ð² Ð¿Ð¾ ÑÐ¾Ð½Ð°Ð»ÑÐ½Ð¾ÑÑÐ¸ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Sentiment analysis with machine learning methods
Creators: name: ÐÐ°Ð»ÑÑÐµÐ½ÐºÐ¾, Ð®Ð»Ð¸Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2022
Subjects: Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
ÑÐµÑÑ LSTM
Ð¼ÐµÑÐ¾Ð´Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÑÐµÐºÑÑÐ¾Ð²
Ð°Ð½Ð°Ð»Ð¸Ð· ÑÐ¾Ð½Ð°Ð»ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÐºÑÑÐ°
machine learning
neural networks
LSTM network
text classification methods
sentiment analysis

description: Ð¢ÐµÐ¼Ð° ÑÐ°Ð±Ð¾ÑÑ: Â«ÐÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ñ ÑÐµÐºÑÑÐ¾Ð² Ð¿Ð¾ ÑÐ¾Ð½Ð°Ð»ÑÐ½Ð¾ÑÑÐ¸ Ð¼ÐµÑÐ¾Ð´Ð°Ð¼Ð¸ Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸ÑÂ». ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸, ÐºÐ¾ÑÐ¾ÑÐ°Ñ ÑÑÐ¿ÐµÑÐ½Ð¾ ÑÐµÑÐ°ÐµÑ Ð·Ð°Ð´Ð°ÑÑ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° ÑÐ¾Ð½Ð°Ð»ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÐºÑÑÐ°. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ ÑÐµÑÐ°Ð»Ð¸ÑÑ ÑÐ»ÐµÐ´ÑÑÑÐ¸Ðµ Ð·Ð°Ð´Ð°ÑÐ¸: 1. ÐÐ·ÑÑÐµÐ½Ð¸Ðµ Ð»Ð¸ÑÐµÑÐ°ÑÑÑÑ Ð½Ð° ÑÐµÐ¼Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð´Ð»Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÑÐµÐºÑÑÐ¾Ð². 2. ÐÐ½Ð°Ð»Ð¸Ð· ÑÑÑÐµÑÑÐ²ÑÑÑÐ¸Ñ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð¸ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ðµ Ð½Ð°Ð¸Ð±Ð¾Ð»ÐµÐµ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾Ð¹ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ ÑÐµÐºÑÑÐ¾Ð² Ð¿Ð¾ ÑÐ¾Ð½Ð°Ð»ÑÐ½Ð¾ÑÑÐ¸. 3. Ð¡Ð¾Ð·Ð´Ð°Ð½Ð¸Ðµ Ð¸ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð² Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ðµ Ð½Ð° ÑÐ·ÑÐºÐµ Python Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸Ðµ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐº TensorFlow Ð¸ Keras. 4. Ð¢ÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð½Ð° ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ Ð½Ð°Ð±Ð¾ÑÐ°Ñ Ð´Ð°Ð½Ð½ÑÑ, Ð° ÑÐ°ÐºÐ¶Ðµ Ð½Ð° Ð¿ÑÐ¾Ð¸Ð·Ð²Ð¾Ð»ÑÐ½ÑÑ ÑÐµÐºÑÑÐ°Ñ. Ð Ð¿ÑÐ¾ÑÐµÑÑÐµ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð¼Ð¾Ð´ÐµÐ»Ð¸ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð½Ð° ÑÐ·ÑÐºÐµ Python Ð´Ð»Ñ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ Ð½Ð°Ð±Ð¾ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¸Ð· ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ ÑÐ¼Ð¾ÑÐ¸Ð¾Ð½Ð°Ð»ÑÐ½Ð¾ Ð¾ÐºÑÐ°ÑÐµÐ½Ð½ÑÑ ÑÐµÐºÑÑÐ¾Ð². Ð¢Ð°ÐºÐ¶Ðµ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð°ÑÑ Ð¼Ð¾Ð´ÐµÐ»Ñ Word2Vec Ð´Ð»Ñ Ð²ÐµÐºÑÐ¾ÑÐ½Ð¾Ð³Ð¾ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ ÑÐ»Ð¾Ð². Ð ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð° ÑÐ¾Ð·Ð´Ð°Ð½Ð° Ð¼Ð¾Ð´ÐµÐ»Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐ¸ Ð´Ð»Ñ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° ÑÐ¾Ð½Ð°Ð»ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÐºÑÑÐ¾Ð², Ð¾ÑÐ½Ð¾Ð²Ñ ÐºÐ¾ÑÐ¾ÑÐ¾Ð¹ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÑÐµÑ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÐ° LSTM (ÐÐ¾Ð»Ð³Ð°Ñ ÐºÑÐ°ÑÐºÐ¾ÑÑÐ¾ÑÐ½Ð°Ñ Ð¿Ð°Ð¼ÑÑÑ). ÐÐ¾Ð»ÑÑÐµÐ½Ð½Ð°Ñ Ð¼Ð¾Ð´ÐµÐ»Ñ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð»Ð° Ð´Ð¾ÑÑÐ°ÑÐ¾ÑÐ½Ð¾ Ð²ÑÑÐ¾ÐºÐ¸Ðµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð½Ð° ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÑ ÑÐµÑÑÐ¾Ð²ÑÑ Ð´Ð°Ð½Ð½ÑÑ.
description: The topic of the work: "Sentiment analysis with machine learning methods". This work is devoted to the creation of a neural network model that successfully solves the problem of text sentiment analysis. During the work the following tasks were solved: 1. Studying the literature on the topic of various machine learning methods for text classification. 2. Analysis of existing neural networks and creation of the most efficient neural network model for classifying texts by sentiment. 3. Creating and training a neural network in a Python program using the TensorFlow and Keras libraries. 4. Testing the model on various datasets, as well as on arbitrary texts.In the process of creating a neural network model in Python datasets from various emotional texts were used for training. In addition, the Word2Vec model was used for vector representation of words. As a result of the work, a neural network model was created for sentiment analysis, the basis of which is the LSTM (Long Short-Term Memory) architecture. The resulting model showed high results on various test data.