Using data of articles from 42 Social Science Citation Index (SSCI)-indexed journals of applied linguistics, this study renders a bibliometric analysis of the 2005–16 research trends in the field. The analysis focuses on, among other issues, the most frequently discussed topics, the most highly cited publications, and the changes that have occurred in the research trends. The results show that while most of the frequently discussed topics have remained popular over the 12 years, some (especially sociocultural/functional/identity issues) have experienced a significant increase of interest, but some others (particularly certain phonological/grammatical/generative linguistic topics) have witnessed a substantial decrease of interest. There has also been an increased use of new theories including those coming from distant disciplines. Furthermore, while the number of publications from traditional publication powerhouses, such as the USA, has shown a slow, albeit steady decline proportionally, those from some other countries, such as China, have exhibited a substantial steady rise. The latter countries’ increasing publication rates appear to have contributed to the increased discussion of issues specific to their context. Implications of the findings are also discussed.

Topic modelling is a powerful text mining tool that has been applied in many fields such as software engineering, political and linguistic sciences. To evaluate the development of topic modelling studies, the present study reports a bibliometric analysis of SCIE, SSCI and A&HCI listed articles published from 2000 and 2017. Bibliometric indices for productive authors, countries and institutions are analysed. In addition, thematic changes concerning topic modelling are also examined. Results show that China plays a leading role in this field. Topic modelling has established itself as an important technique in not only natural and formal sciences but also social sciences. LDA, social networks and text analysis are the topics with increasing popularity, while certain models (e.g. pLSA) and applications (e.g. topic detection) are declining in popularity. The findings could help researchers optimise research topic choices, seek collaboration with appropriate partners and stay up-to-date with the development of the field.