Attitudes on Animal Welfare’s Messages in the English Caption Text of @jakartaanimalaidnetwork Instagram’s Account
Abstract
With the growing global concern for animal welfare, social media platforms like Instagram are crucial in raising awareness and promoting advocacy. This research investigates the attitudes conveyed in animal welfare messages through the English caption texts on the @jakartaanimalaidnetwork Instagram account. The study aims to identify how the Appraisal System in Systemic Functional Linguistics (SFL) expresses attitudes in these captions, focusing specifically on the categories of Affect, Judgment, and Appreciation. A qualitative descriptive research design was used, with data collected from English captions relevant to animal welfare. Content analysis was employed to categorize the captions based on their emotional (Affect), evaluative (Judgment), and appreciative (Appreciation) contents. The study utilized domain, taxonomy, componential, and cultural theme analysis to interpret the attitudes expressed in the captions. The results revealed that Affect was the most dominant category, with frequent expressions of emotions such as happiness, sadness, and empathy towards the animals. Judgmental expressions, particularly regarding moral evaluation, were also prevalent, reflecting the organization's ethical stance on animal treatment. Appreciation was expressed through a positive animal care assessment, emphasizing the value and quality of animal welfare. Overall, the study highlights the organization's commitment to advocating for the humane treatment of animals, using language that emphasizes compassion, ethical responsibility, and respect for animal rights. These findings demonstrate how the account conveys a clear and supportive message for animal welfare through its use of linguistic attitudes.
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