A Cross-Cultural Pragmatic Study of Indirect Complaint Responses in Iranian and American News Interviews: Iran’s Nuclear Negotiations
Publish Year: 1398
Type: Journal paper
Language: English
View: 163
This Paper With 15 Page And PDF Format Ready To Download
- Certificate
- I'm the author of the paper
Export:
Document National Code:
JR_JFL-7-26_003
Index date: 29 August 2021
A Cross-Cultural Pragmatic Study of Indirect Complaint Responses in Iranian and American News Interviews: Iran’s Nuclear Negotiations abstract
The present study intended to compare the complaint responses used by President Rouhani and President Obama in the Iranian and US news interview contexts. For this purpose, Boxer’s (1993) six types of indirect complaint responses were adopted: ‘ignorance’, ‘questions’, ‘topic switch’, ‘contradiction’, ‘joke/teasing’, ‘advice/lecture’ and ‘agreement/commiseration’. The transcripts of the live news interviews were selected from Tehran Times in Iran and ‘The New York Times’, ‘The Atlantic Daily’, and ‘National Public Radio’ all carried out in 2015. The results of quantitative and qualitative data analyses revealed both universal and culture-specific responses. Whereas both nations made nearly equal use of ‘question’ response in order to make solidarity, ‘contradiction’ was used most frequently in the US interviews and ‘topic-switch’ and ‘commiseration’ were more frequent in Iranian transcripts. The findings are discussed with respect to the culture-specificity and universality and the way that news interviews deal with the political information including Iran’s nuclear negotiations.
A Cross-Cultural Pragmatic Study of Indirect Complaint Responses in Iranian and American News Interviews: Iran’s Nuclear Negotiations Keywords:
A Cross-Cultural Pragmatic Study of Indirect Complaint Responses in Iranian and American News Interviews: Iran’s Nuclear Negotiations authors
Hadis Toofani Asl
Department of Foreign Languages, Shanghai University. Shanghai, China
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :