Lexical And Syntactical Ambiguity In The Headlines Of Cnn

Abstract

This study dealt with Lexical and Syntactical Ambiguity in the Headlines of CNN. The aims of this research were to find out the types of lexical and syntactical ambiguity in the headlines of CNN and to find out the dominant type of ambiguity in the headlines of CNN. The data were taken from headlines of CNN from Mei 2018 till April 2019. The numbers of data were 24 headlines which was taken 2 headlines per month. The types of ambiguity were identified based on Saeed and Kreidler theory. The research applied a qualitative descriptive that established the requirement that a study must be carried on the basis existing fact. The method used to collect data was documentation. The techniques of collecting data were choosing, reading and underlining. The data were analyzed by identifying, classifying, analyzing, calculating, and interpreting. From 24 headlines there were 21 headlines that contained ambiguous meaning and 3 of them had no ambiguous meaning. In some headlines there were two types of ambiguity both lexical and syntactical ambiguity. There were 17 sentences were lexically ambiguous, while the other 11 sentences were syntactically ambiguous, so the most dominant was lexical ambiguity. The lexical ambiguity consisted of homonymy, polysemy, synonymy, and antonym. While, syntactical ambiguity consisted of surface structure ambiguity and deep structure ambiguity.