LEXICAL COHESION IN POLOTICAL NEWS FOUND IN CNN ONLINE ARTICLES

Dewi, Aminah (2017) LEXICAL COHESION IN POLOTICAL NEWS FOUND IN CNN ONLINE ARTICLES. Undergraduate thesis, UNIVERSITAS 17 AGUSTUS 1945 SURABAYA.

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Abstract

This thesis provides and analysis of lexical cohesion in 5 political news articles which are taken from CNN online articles. Those articles are taken with different topic but they all are based on political issue during Trump’s administration. The aims of this thesis is to indetify the type and the contribution of lexical cohesion in giving the cohesiveness in the text. It applies the descriptive qualitative approach. This study found 117 data consists of repetition, synonym or near synonym, superordinate, general word and collocation. From data A1 is found 1 data 18 data for repetition, 8 data for synonym and near synonym, 3 data for superordinate, 1 data for general word and 2 data for collocation. Data A2 is found 19 data for repetition, 4 data for synonym and near synonym, 4 data for superordinate, 2 data for general word and 2 data for collocation. Data A3 is found, 15 data for repetition, 6 data for synonym and near synonym, 1 data for superordinate, and 2 data for collocation. Data A4 is found 8 data for repetition, 1 data for synonym and near synonym, and 1 data for general word. Data A5 is found 10 data for repetition, 1 data for synonym and near synonym, 1 data for general word and 1 data for superordinate. Those data contribute to build the topic of each text by the relation of its presupposing and presupposed items and the context of the events that occurs in the text.

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