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Code-Switching Made By Indonesian Influencers On Youtube Miranda Kristin Lumban Tungkup; Bertaria Sohnata Hutauruk; Tiarma Intan Marpaung
Jurnal Ilmu Sosial dan Humaniora Vol. 4 No. 2 (2026): April
Publisher : CV Putra Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58540/isihumor.v4i2.1626

Abstract

This research aims to analyze the types of code-switching and the reasons for using code-switching found on YouTube channels by Indonesian influencers, namely Fathia Izzati Saripudin and Najwa Shihab. This research uses qualitative descriptive research. Data were taken from the transcripts of two YouTube videos featuring FIS and NS. The analysis focused on the types and reasons of code-switching based on Hoffman’s theory (1991), which classifies code-switching into three types: inter-sentential code-switching, intra-sentential code-switching, and tag-switching, as well as seven reasons for its use, namely talking about a particular topic, quoting somebody else, being emphatic about something, interjection, repetition used for clarification, expressing group identity, and intention of clarifying speech content for the interlocutor. The results showed that in FIS’s utterances, intra-sentential code-switching was the most dominant type with 117 data (77.48%), followed by inter-sentential code-switching with 33 data (21.85%), and tag-switching with 1 data (0.66%). Similarly, in NS’s utterances, intra-sentential code-switching was also the most dominant type with 28 data (84.85%), followed by tag-switching with 3 data (9.09%), and inter-sentential code-switching with 2 data (6.06%). Furthermore, in FIS’s utterances, the most dominant reason was talking about a particular topic with 76 data (50.33%), followed by being emphatic about something with 56 data (37.08%), intention of clarifying speech content for the interlocutor with 6 data (3.97%), quoting somebody else with 5 data (3.31%), repetition used for clarification, and expressing group identity each has 3 data (1.99%) and the last is interjection with 2 data (1.32%). In NS’s utterances, the most dominant reason was being emphatic about something with 19 data (57.58%), followed by talking about a particular topic with 6 data (18.18%). Quoting somebody else, intention of clarifying speech content for the interlocutor, and interjection each occurred 2 times (6.06%), while expressing group identity and repetition used for clarification each occurred once (3.03%). This research concludes that code-switching is not merely a speaking style but also serves as an important communicative strategy in digital media, reflecting how influencers manage interaction and adapt their language to audience needs, thereby enhancing communication effectiveness.
Forensic Linguistics Study: Online Hate Speech On Social Media Instagram (Indonesian Government) Elisabeth Dwi Clara; Bertaria Sohnata Hutauruk; Melda Veby Ristella Munthe
Jurnal Ilmu Sosial dan Humaniora Vol. 4 No. 2 (2026): April
Publisher : CV Putra Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58540/isihumor.v4i2.1627

Abstract

The increasing use of social media as a public communication space has led to the widespread emergence of hate speech, particularly in Instagram comment sections related to government issues. This research aims to analyze manifestations of hate speech through illocutionary acts on the Instagram accounts @presidenrepublikindonesia and @kemensetneg_ri, classify their forms based on the National Police Chief’s Circular Letter No. SE/06/X/2015, and identify the most dominant types found in the data. This research employs a qualitative descriptive approach supported by quantitative analysis. The data consists of 200 Instagram comments collected from posts related to public policy and government activities. Analysis was conducted using a pragmatic approach based on illocutionary acts, specifically expressive, directive, and assertive acts as proposed by John Searle, and further classified into categories of hate speech such as insults, defamation, and provocation. The results of the research indicate that expressive speech acts are the most dominant, suggesting that users primarily express negative emotions such as anger, disappointment, and sarcasm. In terms of hate speech classification, insults emerged as the most frequent category, followed by defamation and provocation. Although most of the statements do not fully meet the legal criteria under the ITE Law, they still have the potential to cause negative effects in digital communication. These findings indicate that the line between criticism and hate speech remains unclear among social media users and highlight the importance of understanding language use in a digital context.