Social Media Sentiment Analysis with Context Space Model

Анна Васильевна Мальцева, Наталья Егоровна Шилкина, Олеся Владимировна Махныткина, Инна Лизунова

Результат исследований: Научные публикации в периодических изданияхстатьярецензирование

1 Цитирования (Scopus)


In this article the description of algorithm of an assessment of mood of the statement is presented with the accent on the context of user’s messages in social media. The article focuses on the fact that messages containing identical sentiment objects have different meaning that affects onto the evaluation of the sentiment of the message. An additional research objective is the identification of formal criteria for assigning messages to classes “core”, “periphery”, “non-relevant” to denote the role of the research relevance of the object key in the message. In this article, we have given several examples of authentic messages for each group. The method was tested on the empirical basis of more than 10,000 messages to assess the relationship of users of the social network VKontakte to the object of tonality – a form of employment “freelance”. The research methodology presupposes the use of basic and additional methods of data preprocessing, data augmentation, comparative analysis of the application of classification methods. The article includes comparative description of results of application logistic regression, support vector machines, naive Bayesian classifier, nearest neighbor, random forest.

Язык оригиналаанглийский
Страницы (с-по)399-412
Число страниц14
ЖурналCommunications in Computer and Information Science
Том1135 CCIS
СостояниеОпубликовано - 1 янв 2020

Предметные области Scopus

  • Прикладные компьютерные науки
  • Социология и политические науки
  • Математика (все)
  • Компьютерные науки (все)

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