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dc.contributor.authorSALSABILA, Ais Aurelia
dc.date.accessioned2024-06-03T04:21:37Z
dc.date.available2024-06-03T04:21:37Z
dc.date.issued2023-07-15
dc.identifier.nim190110101043en_US
dc.identifier.urihttps://repository.unej.ac.id/xmlui/handle/123456789/120824
dc.descriptionvalidasi_repo_firli_november_2023_16en_US
dc.description.abstractThis research analyzes the code-mixing phenomenon inside the Instagram captions that the millennials made and posted. This research object is the sixtythree posts, precisely the captions of millennials on Instagram. The posts were posted from January 2020 until January 2023 by millennials on Instagram. This research aims to find out the types used by the millennials using Muysken‟s (2000) theory about the types of code-mixing. This research also aims to reveal the millennials‟ reasons for doing code-mixing using Hoffman‟s (1991) and Troike‟s (1986) theories. This study is considered qualitative research. The data were taken from 63 non-commercial posts with mixed language inside the captions and posted by millennials or Generation Y. Those data inside the posts were collected through documents. While the other data, the reasons for doing code-mixing, were collected through a questionnaire in Google Forms. After that, the data that had been collected were analyzed using Muysken‟s (2000) theory. He proposed three types of code-mixing, insertion, alternation, and congruent lexicalization. Secondly, the result of the questionnaire is analyzed using the theories of codemixing reasons proposed by Hoffman (1991) and Troike (1986). The result shows that 32 data are considered as insertion type, 39 are considered as alternation type, and 26 are considered as congruent lexicalization type. According to the percentage, the most used type is alternation. While the result of the questionnaire shows that 27 of 28 participants are millennials or Generation Y, and there are seven reasons were chosen by 25 participants as their reasons for doing code-mixing. Those reasons are real lexical needs (48%), talking about a particular topic (16%), quoting somebody else (12%), interjection (8%), to exclude other people when a comment is intended for only a limited audience (8%), be emphatic about something (4%), and others (4%).en_US
dc.description.sponsorshipReni Kusumaningputri, S.S., M.Pd. Dewianti Khazanah, S.S., M.Hum.en_US
dc.language.isoenen_US
dc.publisherFakultas Ilmu Budayaen_US
dc.subjectCode-mixingen_US
dc.subjectSociolinguisticsen_US
dc.subjectInstagramen_US
dc.subjectLanguage Contacten_US
dc.titleThe Analysis of Code-mixing in Millennials' Captions on Instagramen_US
dc.typeSkripsien_US
dc.identifier.prodiSastra Inggrisen_US
dc.identifier.pembimbing1Reni Kusumaningputri, S.S., M.Pd.en_US
dc.identifier.pembimbing2Dewianti Khazanah, S.S., M.Hum.en_US
dc.identifier.validatorvalidasi_repo_firli_november_2023_16en_US
dc.identifier.finalization0a67b73d_2024_06_tanggal 03en_US


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