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Implicit vs explicit evaluation: How English-speaking Twitter users discuss migration problems
The current research answers the question how Twitter users express their evaluation of the topical social problem (explicitly or implicitly) and what linguistic means they use being restricted by the limited length of the message. The article explores how Twitter users socialize with each other and exchange ideas on social issues of great importance, express their feelings using a number of linguistic means while being limited to 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 to express their personal attitudes to 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 attempted to define which tools contributed to implicit or explicit nature of the utterances. The research is based on the content analysis of 100 tweets of English-speaking users collected from February, 1 to July, 31 2017 and done through the program Atlas.ti. The software performs coding of textual units, counting the frequency of codes and their correlation. The choice of the period is defined by significant events in Trump’s migration policy and its consequences. The results of the research show that Twitter users tend to express critical attitudes towards migration rather than approve of it or sympathize 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 imperative structures were used to declare attitudes explicitly. It is also worth mentioning that ellipsis, contractions and abbreviations were used quite frequently which is due to the word limit of tweets. Even though people have an opportunity to send messages anonymously they still tend to imply their negative attitude towards political authorities. 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.