Abstract:

The current research answers the question how Twitter users express their evaluation of topical social problems (explicitly or implicitly) and what linguistic means they use, being restricted by the allowed length of the message. The article explores how Twitter users communicate with each other and exchange ideas on social issues of great importance, express their feelings using a number of linguistic means, while being limited by a fixed number of characters, and form solidarity, being geographically distant from each other. The research is focused on the linguistic tools employed by Twitter users in order to express their personal attitude. The subject chosen for study was the migration processes in Europe and the USA. The aim of the current investigation is to determine the correlation between the attitudes of English-speaking users towards migration and the way they are expressed implicitly or explicitly. The authors make an attempt to define which tools contribute to the implicit or explicit nature of the utterances. The material includes 100 tweets of English-speaking users collected from February 1 to July 31, 2017. The choice of the time period is defined by significant events in Trump’s migration policy and their consequences. The research is based on the content analysis of the material carried out by means of the Atlas.ti program. The software performs the coding of textual units, counts the frequency of codes and their correlation. The results of the research show that Twitter users tend to express their critical attitudes towards migration, rather than approve of it or sympathise with migrants. Criticism is more often expressed implicitly rather than explicitly. In order to disguise the attitude and feelings, the English-speaking users of Twitter employed irony, questions and quotations, while the explicit expression of attitudes was done by means of imperative structures. It is also worth mentioning that ellipses, contractions and abbreviations were used quite frequently due to the word limit of tweets. At the same time, the lack of knowledge about extralinguistic factors and personal characteristics of users makes the process of interpretation of tweets rather challenging. The findings of the current research suggest the necessity to take into account implicit negative attitudes while carrying out the analysis of public opinion on Twitter.

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