Bibliometric studies analyzing research trends often assume regional characteristics significantly influence these trends. In 'language and linguistics', regional factors may be especially impactful, given the inherent connection between language and culture. While numerous bibliometric studies exist on specific subtopics within language and linguistics, regional trends, particularly in Asia, remain understudied. Asia's linguistic diversity, with languages largely outside the Indo-European family, presents a unique case for study. This research aims to comprehensively analyze 'language and linguistics' research trends in 13 diverse Asian countries over two decades, considering productivity, authorship, collaboration, keywords, and research impact. Previous studies, such as those by Barrot (2017) and Lei and Liao (2017), examined limited subsets of Asian countries or focused on specific subtopics, limiting their scope. This study addresses these limitations by using a much larger dataset covering 13 of the most prolific Asian countries in the field.

Existing bibliometric analyses of 'language and linguistics' research often focus on specific subfields like children's language, computational linguistics, discourse analysis, ELT, linguistic landscape, natural language processing, second language acquisition, second language writing, and vocabulary acquisition. Other studies concentrated on the intersection of linguistics and computer science, investigating areas such as chatbots, computational linguistics, natural language processing, sentiment analysis, and topic modeling. While some studies have attempted regional-level analyses, they often suffered from limited sample sizes or geographical scope. For example, Barrot (2017) studied Southeast Asia, and Lei and Liao (2017) focused on four Chinese-speaking regions. These studies lacked the comprehensive scope of this research, which aims to fill the critical gap in the literature by providing a large-scale, multi-faceted bibliometric analysis of 'language and linguistics' research across 13 diverse Asian countries.

This study selected 13 Asian countries based on their R&D spending (exceeding 0.5% of GDP, with exceptions for Taiwan, Indonesia, and Saudi Arabia). Data was collected from Elsevier's Scopus, using a search strategy combining country affiliation and keywords related to 'language and linguistics'. The study focused on journal articles published from 2000 to 2021, excluding articles from predatory journals. Articles were categorized as published in either 'international' or 'regional' journals based on WoS indexing. A total of 30,515 articles were analyzed. Authorship patterns were determined by the first author's affiliation, with manual verification for corresponding authors. Citation data was collected from Scopus, using a five-year citation window for articles published before 2016. Keywords were extracted either from author-provided keywords or, where unavailable, using the KeyBERT method, based on the BERT algorithm. Analysis methods included examining publication counts, authorship patterns, collaboration networks, keyword frequencies, and citation counts. Self-citations were analyzed at both the author and country levels. Collaboration networks were analyzed using modularity-based community detection to identify clusters of countries with similar collaboration patterns.

The 13 selected countries accounted for 85.2% of all 'language and linguistics' publications in Asia from 2000 to 2021, significantly outweighing the output of the remaining 28 Asian countries. China, Japan, Hong Kong, and Taiwan were the most prolific, publishing heavily in international journals. Indonesia, Iran, and Malaysia published more in regional journals. Traditionally, research focused on national languages and dialects. Since 2010, research on English has significantly increased. High levels of collaboration existed both within Asia and with Western countries. The most frequent authorship pattern was sole authorship (35.7%), followed by two-author (31.1%) and three-author (17.3%) collaborations. However, the trend shows an increase in co-authorship over time. The international collaborations between Asian countries with the United States, the United Kingdom, and Australia were significant. The most common keywords were related to Asian languages, English language learning ('EFL'), discourse analysis, and language education. Since 2010, English-related topics and discourse analysis have gained prominence, while traditional linguistic components have decreased in relative importance. Regarding research impact, Hong Kong, Israel, and Singapore's articles received the most citations. Indonesia, Iran, and Malaysia demonstrated high domestic impact, while Saudi Arabia, Singapore, South Korea, and Turkey showed significant international impact. The United States was the top citing country for all 13 Asian countries.

This study's findings address the lack of comprehensive bibliometric analysis of Asian 'language and linguistics' research. The dominance of the 13 selected countries in the field justifies focusing on their research trends. The shift toward English-related topics reflects globalization and the increasing importance of English as a lingua franca. The high rates of international collaboration highlight the interconnectedness of the global 'language and linguistics' research community. The varying citation patterns reflect the differing levels of international and domestic impact, with some countries showing greater success in attracting international attention.

This study provides a comprehensive bibliometric analysis of 'language and linguistics' research in 13 key Asian countries over two decades. The findings reveal the field's regional dominance, the increasing importance of English, and diverse patterns of collaboration and impact. Future research could use topic modeling to explore collaborative relationships further, investigate the factors determining research impact in the field, and measure the growing impact of Asian 'language and linguistics' research on cutting-edge Computer Science technologies.

The study's reliance on Scopus data may introduce limitations regarding the complete coverage of all publications, particularly regional journals not indexed in Scopus. The five-year citation window for impact analysis may not fully capture the long-term impact of some publications. The use of KeyBERT for keyword extraction in some articles, although validated, could have introduced minor biases. Further research focusing on domestic citation patterns within each country could offer deeper insights.