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ANALYZING SOCIOLINGUISTIC FEATURES: THE USE OF REGISTER IN ONLINE COMMERCIAL DISCOURSE AND ITS APPLICATION IN ENGLISH LANGUAGE TEACHING

Authors: Ikrar Genidal Riadil;

ANALYZING SOCIOLINGUISTIC FEATURES: THE USE OF REGISTER IN ONLINE COMMERCIAL DISCOURSE AND ITS APPLICATION IN ENGLISH LANGUAGE TEACHING

Abstract

The language used in digital marketing, particularly on social media platforms like Instagram, reflects unique patterns that differ significantly from everyday spoken interaction. This study aims to explore how linguistic registers are used in commercial communication on Instagram, focusing on the account @dailyluxury_id. It also examines how these registers can be utilized in English language teaching. Using a qualitative descriptive method, the study analyzed 50 Instagram captions posted between January and March 2024. Content analysis was employed to identify and classify the registers based on word types (such as nouns and verbs) and their meanings, which were grouped into two categories: lexical (dictionary-based) and contextual (influenced by marketing purposes). The results show that 11 frequently used words appeared, with nouns (36.36%) and verbs (18.18%) being the most common, reflecting a focus on promotion and transaction. About 54.54% of the meanings followed standard dictionary definitions, while 45.45% had contextual meanings that conveyed urgency, exclusivity, or community engagement. For example, the word ready implies immediate availability, while local lovers create a sense of belonging. These language strategies contribute to a conversational yet persuasive tone that supports digital marketing goals. The study concludes that the use of registers on Instagram is purposeful and adapted to the target audience. It also suggests that such linguistic features can be integrated into English language teaching to expose learners to authentic, socially relevant materials—particularly in courses related to sociolinguistics, digital communication, or business English.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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