Automated Detecting of Key concept of Kurdish National Identity for Discourse-Historical Approach (DHA)
This study aims to utilize the keyness technique in the Wmatrix corpus software for detecting data-driven extracted texts for the in-depth analysis of DHA to understand how Kurds construct their national identity after the independence referendum of the Kurdistan Region of Iraq. Applying the computer-assisted corpus analysis (CACA) method proposed by Manvender (2014), the study utilised the automated semantic tagger (USAS) embedded in Wmatrix corpus software is to overcome the cherry-picking criticism to CDA, namely selecting extract based on the researchers’ intuitions which jeopardize the scientific credibility of the study. The source of data for this study is from two focused group interviews. Each group comprises five Kurdish members who are involved in the study program of master and PhD in Utara University Malaysia (UUM). Key concepts with the concordance of high significant frequency items are assigned for further analysis through DHA which examines discourse not only at the internal textual level but at extra-linguistic as well as socio-political and historical context levels; to connect the discourse to its environment which constitute it. The findings displayed that the USAS successfully achieved the objective for which it employed, moreover, the software exposed area for in-depth analysis which could have been overlooked otherwise. As this study is to report the evidence from qualitative analysis, the findings disclosed that the informants heavily depend on categorization, metaphors, and deixis to establish inclusion and exclusion groups as well as on topoi and legitimization for argumentation strategies to justify the presentation they demonstrated for in- and out-groups.