СЕНТИМЕНТ АНАЛИЗ: ПРОБЛЕМЫ И РЕШЕНИЯ - Проблемы Информационных Технологий

СЕНТИМЕНТ АНАЛИЗ: ПРОБЛЕМЫ И РЕШЕНИЯ - Проблемы Информационных Технологий

СЕНТИМЕНТ АНАЛИЗ: ПРОБЛЕМЫ И РЕШЕНИЯ - Проблемы Информационных Технологий

СЕНТИМЕНТ АНАЛИЗ: ПРОБЛЕМЫ И РЕШЕНИЯ - Проблемы Информационных Технологий

СЕНТИМЕНТ АНАЛИЗ: ПРОБЛЕМЫ И РЕШЕНИЯ - Проблемы Информационных Технологий
СЕНТИМЕНТ АНАЛИЗ: ПРОБЛЕМЫ И РЕШЕНИЯ - Проблемы Информационных Технологий
НАЦИОНАЛЬНАЯ АКАДЕМИЯ НАУК АЗЕРБАЙДЖАНА

№2, 2020

СЕНТИМЕНТ АНАЛИЗ: ПРОБЛЕМЫ И РЕШЕНИЯ

Гаджирагимова Макруфа Ш., Исмайылова Марзия И.

Сентимент анализ или интеллектуальный анализ мнений – это область исследований, которая анализирует мысли, чувства, эмоции, оценки и отношения людей, изучает такие объекты, как продукты, услуги, организации, люди, проблемы, события, темы и их характеристики. Развитие анализа настроений связано с появлением большого количества цифровых данных, генерируемых в социальных сетях, на форумах, в блогах, микроблогах и т.д. В последние годы сентимент анализ стал предметом обширных исследований в таких областях, как обработка естественного языка, интеллектуальный анализ данных, анализ текста и поиск информации. Сентимент анализ широко распространен в областях маркетинга, финансов, политологии, общественных наук, медицинских наук и т.д. Такая популярность объясняется тем, что мнения имеют решающее значение практически во всех областях человеческой деятельности и являются основным фактором, влияющим на поведение людей. Неспособность легко анализировать сотни тысяч мнений, опубликованных в социальных сетях, блогах, форумах и других источниках мнений, обусловила необходимость использования компьютерной лингвистики, сентимент анализа или анализа мнений. В статье рассматриваются исторические и терминологические аспекты сентимент анализа, предоставляется информация об источниках информации и областях применения. Основные задачи и уровни сентимент анализа также изучаются в данной работе. Существующие проблемы и решения были проанализированы (стр.111-123).

Ключевые слова: сентимент анализ, анализ мнений, классификация настроений, уровни сентимент анализа, machine learning.
DOI : 10.25045/jpit.v11.i2.11
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