ONLINE VERBALIZATION OF PERSONAL ASSESSMENT: ENGLISH-LANGUAGE TWITTER REACTIONS IN THE PROTEST POLITICAL DISCOURSE
ONLINE VERBALIZATION OF PERSONAL ASSESSMENT: ENGLISH-LANGUAGE TWITTER REACTIONS IN THE PROTEST POLITICAL DISCOURSE

Summary/Abstract: The paper studies the verbalisation of internet users’ personal assessment as a way of affecting public opinion. The authors consider the linguistic means used by the English-speaking internet users of Twitter for expression of their opinion regarding the US Tea Party movement in 2009. As the source of the language material, the authors chose the Twitter social network. The advantages of the microblog as the source of material for the linguistic analysis include the opportunity of selecting the material according to the set parameters (date, topic, and addressers), the completeness and reliability of the sampling, the linguistic diversity for the analysis, the reliability and openness of the text messages. The base for studying the linguistic peculiarities in this paper is the content-analysis of the tweets gathers for the period from February till April 2009. The processing of the collected material was performed using the Atlas.ti software. The authors defined the thematic dominants of the expressions and the expressive means as the markers of the personal opinion of Internet users. The results of the conducted research presented as the diagram illustrate the way for the English-speaking Tweeter users' opinions expression regarding a significant theme of the protest movement for the society and political world. The analysis of the data allows at some themes of the messages were expressed explicitly, however, the critical estimate towards the government and the president of the country were implicated using the linguistic means. Based on the obtained results, the authors of the paper find the answer to the following question: what is the way for the microblog users to affect the opinions of each other through the linguistic expressive means and under the conditions of the text limit of the message down to 140 symbols (as of 2009). The research scientists come to the conclusion that the language estimate is met on Twitter as both positive and negative. Its implicit or explicit expression is achieved through the use of stylistic and syntactic tricks, such as metaphor, comparison, epithet, exclamation, irony, quotations, rhetoric question, and allusion. Special attention here is paid to the study of the interrogative structures as a way of explication or implication of personal opinion.

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