References

ellibs

Электронные библиотеки

Russian Digital Libraries Journal

1562-5419

Казанский (Приволжский) федеральный университет

ellibs-431

Research Article

Статьи

Автоматический анализ тональности текстов по отношению к заданному объекту и его характеристикам

Automatic sentiment analysis towards the entity and its characteristics

Лукашевич

Н. В.

louk_nat@mail.ru

Московский государственный университет им. М.В. ЛомоносоваRussian Federation

2015

28062015

183-488119

2015

Лукашевич Н.В.

Данная работа распространяется под лицензией Creative Commons Attribution 4.0.

This work is licensed under a Creative Commons Attribution 4.0 License.

https://ellibs.elpub.ru/jour/article/view/431

Статья посвящена рассмотрению подходов к анализу тональности текстов по отношению к заданному объекту, а также его характеристикам (аспектам). Для решения задачи анализа тональности по отношению к характеристикам сущности необходимо решать также задачи извлечения аспектов для сущности, категоризацию или кластеризацию аспектов по аспектным категориям, определение тональности текста по отношению к заданному аспекту или аспектной категории. Также в статье описывается задание по анализу тональности отзывов пользователей в рамках открытого тестирования систем анализа тональности SentiRuEval.

The paper considers approaches to sentiment analysis towards a specific entity and its characteristics (aspects). To solve the aspect-oriented sentiment analysis task, it is necessary to extract aspect terms from texts, to classify or cluster aspect terms into aspect categories, to determine the sentiment expressed towards the specfic aspect. The paper also briefly presents SentiRuEval-2015 evaluation of aspect-oriented sentiment analysis systems in Russian.

анализ тональностимашинное обучениетематическое моделированиеоценочная лексика

SentiRuEval

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The authors declare that there are no conflicts of interest present.