A cross-cultural analysis of Turkish and American English electronic complaints: The case study of Amazon website

A large sum of data regarding complaints thus far have been primarily gathered from two mainstream data collection methods: DCTs (discourse completion test) and natural interactive conversations. As a result, written data, more specifically complaints in online environments, have been generally of secondary importance. The thesis paper at hand has attempted to contribute to the investigation of complaints through CMC (computer-mediated communication) which seeks more attention due to the prevalent use of online environments over the two last decades. The major quest in this research is to figure out whether electronic complaints published both on amazon.tr and amazon.com (US) showcase similarities and differences. To obtain relevant findings, a data set of 100 complaints for each language under investigation, Turkish and American English, was qualitatively analyzed with regard to a complaint strategies taxonomy. Based on this classification, these complaints were dichotomized as in/direct. Subsequently, they were analyzed in terms of modification strategies, the use of pronouns and the use of CMC features. The data sets subjected to these five main criteria were later statistically compared. The research results indicate that speakers of Turkish and American English tend to formulate their e-complaints employing direct and indirect complaint strategies in a balance, whereas both parties include a dominance of the use of intensifying features over mitigating features. Keywords: complaints, amazon, computer-mediated communication (CMC), online reviews, speech acts.