Content Analysis of Language-Sensitive Recruitment Influenced by Corporate Language Policy Using Topic Modeling

Abstract

Language-sensitive recruitment is a language management tool frequently used by corporate organizations. However, its relationship with corporate policy is lacking; hence, this study aims to consider language-sensitive job advertisements from a computational text analysis perspective and explore the match (or mismatch) between language-sensitive recruitment (English, Japanese, or bilingual) and corporate language policy. This study uses corpus methods combined with topic modeling and text analysis to investigate the influence of corporate language policy on the textual practice of language-sensitive recruitment in a Japanese multinational corporation (MNC). This study finds a considerable discrepancy between recruitment needs and corporate language policy. It also finds that bilinguals still play a key role in crossing language boundaries 10 years post-mandate of the English language policy in this Japanese MNC. The study contributes to business language by exploring an additional scenario for linking language competency with actual recruitment needs. Thus, this study sheds light on the implementation of language-sensitive recruitment in a multilingual corporate context, affecting the communication patterns and recruitment tactics.