Expressing Opinion on Political Events

Textual, Syntactic and Lexical Analysis

Abstract

Users of forums, social networks and news portals now have the opportunity to publicly express their opinions on current political events, social issues, or their everyday lives. The analysis of opinion expression, which primarily represented a research topic in the field of language learning, has now become an important research challenge in the field of computational linguistics, which provides relevant solutions for various companies and organizations. The aim of this article is to analyse messages by which users of the social network Twitter reacted to an incident in which Emmanuel Macron was slapped in the face by a man as he went out to meet the public. We analysed the tweets that express agreement, disagreement and a neutral attitude towards the action. The analysis includes 80 tweets and refers to the textual, syntactic and lexical levels. The results show that tweets expressing disagreement have a typical declarative or exclamatory form, simple sentence structure and include explicit vocabulary expressing the author’s opinion (shameful, disrespectful). Tweets demonstrating agreement are more likely to have an exclamatory form, simple sentence structure and include an explicit term (well done, deserve a slap). Opinion-neutral tweets, on the other hand, are more likely to be formulated as declarative sentences with complex sentence structure and do not include an explicit term expressing the author’s opinion. The presented method is established on basic grammatical criteria (number of sentences, sentence structure, sentence form, keywords), which can also be applied to computational analysis of large collections of texts. In the future, the presented model could be applied to investigate various political, societal or healthcare challenges (elections, corruption or pandemic issues).