Open access Journal
Systemic Functional Linguistics in Translation Studies Systematic Literature Review
Aptisi Transactions on Technopreneurship (ATT) · Vol. 8 No. 2 (2026) · pp. 617–632
- ISSN
- 2656-8888, 2655-8807
- Published
- 2026-05-26
- Publisher
- Pandawan
- Language
- en
Abstract
Systemic Functional Linguistics (SFL) has become an important tool in Translation Studies. This research conducts a comprehensive literature review to determine the influence of SFL on Translation Studies (TS) and synthesizes existing research to highlight key findings, trends, and gaps in the literature. This study conducted a literature review from 2019 to 2023 concerning the application of SFL in TS. This study applied a systematic literature review method and followed PRISMA to conduct this review. This study used three databases like Scopus, ScienceDirect, and Semantic Scholar. This study also employed qualitative synthesis to analyse the contents of the studies in terms of genres and text type, research foci, theory of SFL and TS used in the research, and methodologies. The study found that authors from China and Indonesia mostly applied SFL in TS. Concerning text type and research foci, novels and poetry have been the most studied, with emphasis on translation quality, translation techniques, and semantic aspects of translation. The theory of SFL, which is mostly used in translation studies, is the interdependency and logical semantics of complex clauses, transitivity, meta function, modulation, theme, and rheme. In addition, translation theory, which is mostly applied in research, includes translation techniques and translation quality assessment. Qualitative research is widely used to explore various aspects of SFL and Translation Studies. This study offers an in-depth analysis of SFL in Translation Studies and identify unexplored areas that could be investigated in the future.
Keywords
Collaboration network of the authors
35 authors · 78 co-authorship links · 8 across different organisations
Hover or tap a name to highlight its co-authors. Double-click to open the author's page.
- Institut Teknologi Sepuluh Nopember
- Lampung University
- Universitas Islam Negeri Raden Intan Lampung
- Universitas Muhammadiyah Metro
- National Research and Innovation Agency
- Affiliation unknown
- Different organisations
- Same organisation
- Affiliation unknown
- Thicker line = more joint articles · bigger circle = more articles
Show as table
| Co-author | Organisation | Joint articles |
|---|---|---|
| Sukron Mazid | Affiliation unknown | 3 |
| Agus Zainal Arifin | Institut Teknologi Sepuluh Nopember | 2 |
| Mimi Mulyani | Affiliation unknown | 2 |
| Nur Efendi | Affiliation unknown | 2 |
| Lenny Nofriyani Adam | Affiliation unknown | 2 |
| Aceng Ruhendi Saifullah | Affiliation unknown | 2 |
| Undang Rosidin | Lampung University | 1 |
| Nina Kadaritna | Lampung University | 1 |
| Nurul Latifah | Universitas Muhammadiyah Metro | 1 |
| Rarasmaya Indraswari | Institut Teknologi Sepuluh Nopember | 1 |
| Dini Adni Navastara | Institut Teknologi Sepuluh Nopember | 1 |
| Mukhlisi | Affiliation unknown | 1 |
| Tri Indri Hardini | Affiliation unknown | 1 |
| Raden Sasnitya | Affiliation unknown | 1 |
| Ratih Laily Nurjanah | Affiliation unknown | 1 |
| Novitasari Novitasari | National Research and Innovation Agency | 1 |
| Hartutik Hartutik | Affiliation unknown | 1 |
| Giri Harto Wiratomo | Affiliation unknown | 1 |
| Eem Munawaroh | Affiliation unknown | 1 |
| Dwi Riyanti | Affiliation unknown | 1 |
| Farikah Farikah | Affiliation unknown | 1 |
| Farikah | Affiliation unknown | 1 |
| Angela Carolina Flores Riquelme | Affiliation unknown | 1 |
| Gusri Ahyar Ibrahim | Affiliation unknown | 1 |
| Gusri Akhyar Ibrahim | Affiliation unknown | 1 |
| Dadang Sudana | Affiliation unknown | 1 |
| Kokok Dj Purwanto | Affiliation unknown | 1 |
| Diden Rosenda | Affiliation unknown | 1 |
| Rustam Rustam | Affiliation unknown | 1 |
| . Susanti | Affiliation unknown | 1 |
Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.