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LingTera
Published by Universitas Negeri Yogyakarta
ISSN : 24069213     EISSN : 24771961     DOI : 10.21831
Core Subject : Education,
Education Languange, Linguistic, Communication & Media
Arjuna Subject : -
Articles 193 Documents
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Verbal bullying 101: Words that wound in the discourse of bullying according to Dhar Mann's videos Allycia Susanti; Sukma Kirani Agna
LingTera Vol 10, No 2 (2023)
Publisher : Department of Applied Linguistics, FBSB, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/lt.v10i2.61450

Abstract

This paper analyses media portrayals of verbal bullying, including its definition, types, and its negative consequences on both the victims and perpetrators, through the lens of Dhar Mann videos. Bullying can be physical, verbal, or relational, and is usually repetitive and involves a power imbalance between the perpetrator and the victim. This paper highlights that the media plays a significant role in shaping the public perception of bullying, and the issue has gained traction through mass media platforms such as YouTube. YouTube has become one of the most famous platforms for establishing current news, entertainment, and educational materials. This paper analyzes the videos that were uploaded to the Dhar Mann YouTube channel, a well-known channel which posts inspirational videos that aim to teach moral lessons. This study reveals that Dhar Mann's videos exhibited different types of verbal bullying and how they occur. Six Dhar Mann videos were chosen and were analysed using a qualitative analysis involving code-scheming and narrative analysis using Krippendorff’s (2018) content analysis framework. It can be concluded that verbal bullying can be classified into taunting, insulting, threatening, blaming, and name-calling. This analysis is expected to establish the foundation for future studies on verbal bullying discourse.
'Hard translation' in Stories to Enlighten the World Aiqing Wang
LingTera Vol 10, No 2 (2023)
Publisher : Department of Applied Linguistics, FBSB, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/lt.v10i2.43850

Abstract

An illustrious figure of Ming-Qing fiction, Feng Menglong (1574-1646), compiled and edited a thought-provoking trilogy of short story anthologies towards the demise of the Ming (1368-1644) dynasty, which contributes to the thriving development of vernacular fiction. The first fascicle of the trilogy is an anthology entitled Stories Old and New (and subsequently Stories to Enlighten the World) that was published in 1620 and translated by Cyril Birch in 1958. In this research, I explore Birch’s rendering that has not attained enough academic attention. I propound that the translation abounds with literal translations and transliterations, which is consistent with the approach of ‘hard translation’ advocated by a renowned writer and translator Lu Xun, aka Zhou Shuren (1881-1936). The ‘hard translation’ strategies can be embodied by Birch’s translation of expressions pertaining to historical personages, religious and literary allusions, as well as sayings and idioms. Furthermore, Birch enriches literal translation and transliteration with illuminating notes and adopts the strategy of adaptation, so as to strike a balance between faithfulness and fluency.
A corpus-based analysis of discourse marker 'like' functions in podcasts: A gender study Zahrotul Nur Azizah Surya Putri; Suray Agung Nugroho
LingTera Vol 10, No 2 (2023)
Publisher : Department of Applied Linguistics, FBSB, Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/lt.v10i2.61245

Abstract

Focusing on the use of discourse markers (DM), this study investigated the use of DM like in dyadic communication in American Spotify podcasts. This research aimed to understand the linguistic behavior of podcasters in using DM like during their podcasts and to compare the spoken corpus of female and male speakers collected from the podcast. Corpus analysis assisted by AntConc 3.5.9. was applied to determine (1) which gender primarily used DM like within the corpus, (2) the significance between the usage of DM like and the speaker’s gender, and (3) the functions of using DM like by each gender based on Müller’s (2005) taxonomy of DM like functions. The analysis portrayed that male speakers prefer to use DM like more than female podcast speakers, which is in contrast to previous studies claiming that female speakers used more DM like than male speakers. The difference in results could be attributed to the 17-year gap in the study, which has potentially led to changes in the inclination of using DM like between genders. However, despite male speakers’ higher usage of DM like, there is still no correlation between the use of DM like and the speaker’s gender, aligning with previous research. Lastly, this study revealed that both genders used the same DM like functions, although the occurrences varied.

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