Research Article
Corpus-Based Research Methodologies in Translation Studies: Issues, Applications, and Prospects
Issue:
Volume 13, Issue 5, October 2025
Pages:
187-194
Received:
21 August 2025
Accepted:
9 September 2025
Published:
30 September 2025
Abstract: The adoption of corpus-based research methodologies in translation studies has prevailed persistently, from which substantial findings have been drawn both internationally and in China. This paper examines this trend by reviewing representative corpus-based research in translation studies, with particular focus on translator style touching translating Chinese classics and on Chinese-foreign language contexts for Chinese and international publications respectively. The findings indicate that the methodologies have incorporated a quantitative perspective, featuring statistical presentation of data, into traditional qualitative analysis, resultantly enhancing the objectivity and credibility of pertinent research. Despite the advantage, certain limitations remain, including restricted multimodal and multilingual capacity, the lack of data consideration and large-scale standardized bilingual corpora, and an overemphasis on quantification, etc. Therefore, this paper contributes by underscoring corpus-based methodologies as reliable and versatile tools able to strengthen translation studies and highlighting the benefits of interdisciplinary innovation and competitiveness in digital humanities for future relevant research.
Abstract: The adoption of corpus-based research methodologies in translation studies has prevailed persistently, from which substantial findings have been drawn both internationally and in China. This paper examines this trend by reviewing representative corpus-based research in translation studies, with particular focus on translator style touching translat...
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Research Article
Ecolinguistic and Critical Discourse Analysis of Environmental Narratives in Sustainable Development Goal Communications
Samuel Oyeyemi Agbeleoba*,
Oluwabukola Orebe,
George Adekunle-Ojo,
Oluwadare Owolabi
Issue:
Volume 13, Issue 5, October 2025
Pages:
195-202
Received:
9 September 2025
Accepted:
22 September 2025
Published:
9 October 2025
Abstract: This study employs an interdisciplinary approach, integrating Ecolinguistic Discourse Analysis (EDA) and Critical Discourse Analysis (CDA), to investigate the ecological and ideological implications embedded within environmental discourses related to the Sustainable Development Goals (SDGs). Analyzing a purposively sampled corpus of official reports, media articles, educational materials, and corporate sustainability reports, the research quantitatively categorizes discourse into three orientations: consonant (60%), neutral (25%), and contravention (15%). Findings reveal that while a majority of texts exhibit consonant discourse, actively promoting ecological sustainability and aligning with the SDGs’ holistic vision, a significant proportion displays neutral discourse characterized by semantic vagueness and mixed messages. Critically, contravention discourse downplays ecological concerns, often privileging economic interests and hindering transformative action. Qualitative analysis, informed by insights from stylistics, pragmatics, and semantics, further elucidates how linguistic choices such as metaphor, framing, and hedging contribute to these discursive positions, shaping perceptions and actions towards environmental sustainability. This study underscores language's powerful role in constructing and contesting ecological realities, arguing for more precise, transparent, and ecologically aligned communication strategies to effectively advance global sustainability goals.
Abstract: This study employs an interdisciplinary approach, integrating Ecolinguistic Discourse Analysis (EDA) and Critical Discourse Analysis (CDA), to investigate the ecological and ideological implications embedded within environmental discourses related to the Sustainable Development Goals (SDGs). Analyzing a purposively sampled corpus of official report...
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,
Huachun Chen
