Title : ( Implied Attitudes in The New York Times Reports on Political Issues Concerning Iran and Israel in 2007: A CDA Approach to Text )
Authors: محمد رحیمی نژاد , Mohammad Ghazanfari ,Abstract
The present study was conducted to see whether is there any underlying meaning in the New York Times political reports which are written on Iran and Israel in 2007, and whether there is any bias in the reports since Iran and Israel are considered America’s opponent and proponent respectively. To do so, 50 reports of the Times were randomly extracted out of the many reports which are available on the Times site www.nytimes.com in 2007. To analyze the reports, the researcher adopted the Hallidayan model as his framework of analysis. The analysis focused on the linguistic choices within the three functions or meanings of Hallidayan model of language. Therefore, the linguistic choices chosen to be analyzed in political reports on Iran and Israel were: active and passive voices, and nominalization within ideational meaning, modality within interpersonal meaning and thematization within textual meaning. After the analysis, the researcher came to this conclusion that the New York Times has used the mentioned features to show its biased attitude towards Iran and Israel.
Keywords
, Key words: critical discourse analysis, media discourse, Hallidayan model of language. Lexical choice@inproceedings{paperid:1020306,
author = {محمد رحیمی نژاد and Ghazanfari, Mohammad},
title = {Implied Attitudes in The New York Times Reports on Political Issues Concerning Iran and Israel in 2007: A CDA Approach to Text},
booktitle = {The 7th International TELLSI Conference},
year = {2009},
location = {یزد, IRAN},
keywords = {Key words: critical discourse analysis; media discourse; Hallidayan model of language. Lexical choice},
}
%0 Conference Proceedings
%T Implied Attitudes in The New York Times Reports on Political Issues Concerning Iran and Israel in 2007: A CDA Approach to Text
%A محمد رحیمی نژاد
%A Ghazanfari, Mohammad
%J The 7th International TELLSI Conference
%D 2009