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Lexical synonymy within the semantic field POWER

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Abstract

The purpose of our paper is to clarify semantic differences in present-day usage between the words<i> &#1088;&#1077;&#1074;&#1086;&#1083;&#1102;&#1094;&#1080;&#1103; </i>&#8216;revolution&#8217;, and <i>&#1087;&#1077;&#1088;&#1077;&#1074;&#1086;&#1088;&#1086;&#1090; </i>&#8216;revolution&#8217;, on the one hand, and <i>&#1084;&#1103;&#1090;&#1077;&#1078; </i>&#8216;revolt&#8217; and <i>&#1074;&#1086;&#1089;&#1089;&#1090;&#1072;&#1085;&#1080;&#1077; </i>&#8216;uprising&#8217;, on the other. Although they are members of the same semantic field, they display some intuitively obvious disparate semantic features. However, these features are only partly registered in dictionaries. On the basis of present-day text corpora, we are going to describe the most relevant semantic differences between these words. We are also going to identify some possible diachronic shifts that have occurred over the last hundred years.An important element in present-day usage of the four words is evaluation, which is usage-biased towards the positive or negative pole. This leaves considerable room for manipulation. One and the same event can be presented as a positive or a negative change in the political world, as initiated by people or inspired and organised by a small group of politicians. The words <i>&#1088;&#1077;&#1074;&#1086;&#1083;&#1102;&#1094;&#1080;&#1103; </i>&#8216;revolution&#8217;, <i>&#1087;&#1077;&#1088;&#1077;&#1074;&#1086;&#1088;&#1086;&#1090;</i> &#8216;coup&#8217;, <i>&#1084;&#1103;&#1090;&#1077;&#1078; </i>&#8216;revolt&#8217; and <i>&#1074;&#1086;&#1089;&#1089;&#1090;&#1072;&#1085;&#1080;&#1077; </i>&#8216;uprising&#8217; are ideal instruments for achieving such purposes and are therefore an important means of manipulating public opinion. Revealing the semantic mechanisms behind this manipulation is a central issue in the linguistic investigation of Russian political discourse. Keywords: lexical semantics; pragmatic shifts; lexicography; near-synonyms; corpus-based co-occurrence analysis; manipulating public opinion

References

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