Mapping the knowledge domain of multimodal translation: a bibliometric analysis

Abstract

To investigate the landscape of the studies on multimodal translation, 2573 papers extracted from the Web of Science (WoS) from 1990 to 2023 in related research were analyzed from the dimensions of the characteristics of publication, co-citations, and co-occurring terms using the bibliometric approach. The result indicates that the annual publications on multimodal translation have grown sharply, particularly in the last ten years (2012–2023). Meanwhile, the five top co-cited researchers and their works stand out from the dataset analyzed with three indicators: citation frequency, betweenness centrality, and citation burstness. Furthermore, the analysis of co-citation clustering reveals a notable tendency to prioritise research trends in the domain of subtitling in films and other streaming media. These research trends are predominantly characterized by corpus-based analysis and audience reception study. The hot topics include audiovisual texts, media accessibility, reception research, and language learning in a multimodal translation context. Under the discussion of the research results from the experimental research methods, research medium, and metafunctional approach, suggestions for future studies are provided.