Keywords
Systemic Functional Linguistics
social media discourse
hashtags
linguistic identity
attitude
affect
engagement
How to Cite
Article History
Abstract
This study investigates the language encoding of emotional states by Turkish Twitter users through the hashtag #depresyondayım ("I am depressed"), utilizing Martin and White's (2005) Appraisal Framework within Halliday's (1978) Social Semiotic perspective. This research utilizes Systemic Functional Linguistics to examine how users employ attitudinal resources, engagement methods, and graduation procedures as semiotic tools to articulate emotional pain, negotiate social roles, and create identities in digital environments. A qualitative analysis of 130 tweets indicates that the content primarily consists of affect resources (81.5%), monoglossic engagement (84.6%), and force-based graduation (67.7%). Notable linguistic patterns were identified across seven thematic categories: everyday frustrations, economic hardships, emotional isolation, academic/work stress, seasonal effects, societal issues, and social deprivation. The research illustrates how the Appraisal Framework elucidates the intricate relationship among emotion, evaluation, and intensification in digital communication, while exposing how depression discourse operates as a multifaceted semiotic resource fulfilling diverse social functions beyond the expression of clinical distress. This study aims to contribute to digital discourse analysis by applying the Appraisal Framework to Turkish social media texts. In the process, observations were made about the role of Turkish morphological and syntactic features in evaluative language use.
Öz
Bu çalışma, Türk Twitter kullanıcılarının #depresyondayım etiketi aracılığıyla duygusal durumlarını dilsel olarak nasıl kodladıklarını Halliday'in (1978) Sosyal Göstergebilim perspektifinde Martin ve White'ın (2005) Değerlendirme Kuramını kullanarak incelemektedir. Dizgeci İşlevsel Dilbilime dayanan bu araştırma, kullanıcıların duygusal durumlarını ifade etmek, sosyal konumlarını tartışmak ve dijital alanda kimliklerini inşa etmek için tutum kaynaklarını, etkileşim stratejilerini ve derecelendirme tekniklerini göstergebilimsel kaynaklar olarak nasıl kullandıklarını araştırmaktadır. Bulgular, 130 tweetin nitel analiz yoluyla, tweetlerin ağırlıklı olarak duygulanım kaynakları (%81,5), tekdilli bağıntılaşım (%84,6) ve güç-temelli derecelendirme (%67,7) içerdiğini ve başta günlük hayal kırıklıkları, ekonomik zorluklar, duygusal izolasyon, akademik/iş stresi, mevsimsel etkiler, toplumsal sorunlar ve sosyal yoksunluk olmak üzere yedi tematik kategoride farklı dil örüntülerinin ortaya çıktığını göstermektedir. Araştırma, Değerlendirme Kuramının dijital iletişimde duygulanım, değerlendirme ve yoğunlaşma arasındaki karmaşık etkileşimi nasıl etkili bir şekilde aydınlattığını gösterirken, depresyon söyleminin ruhsal sıkıntıyı ifade etmenin ötesinde çeşitli sosyal amaçlara hizmet eden değerli bir göstergebilimsel kaynak olarak nasıl işlev gördüğünü ortaya koymaktadır. Bu çalışma, Değerlendirme Kuramını, Türkçe sosyal medya metinlerine uygulayarak dijital söylem analizine katkıda bulunmayı amaçlamaktadır. Bu süreçte ayrıca, Türkçenin biçimbilimsel ve sözdizimsel özelliklerinin değerlendirici dil kullanımındaki rolü hakkında gözlemler yapılmıştır.
Anahtar Kelimeler: Değerlendirme Kuramı, Dizgeci İşlevsel Dilbilim, sosyal medya söylemi, etiketler, dilsel kimlik, tutum, duygulanım, bağıntılaşım
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