Sentiment Analyses of Linguistic Ostracism and Employee Voice Behavior in Pakistani Employees Working Abroad

Abstract

Linguistic ostracism remains a major psychological and linguistic challenge among immigrant workers, affects their social lives, well-being and productivity at work. Between 2022 and 2025, around 2.9 million Pakistanis left the country for employment. Previous researches on Pakistan had largely overlooked linguistic ostracism's impact on employee voice behavior among expatriates particularly utilizing sentiment analysis method. It made linguistic ostracism a crucial topic for scholarly investigation in Pakistani immigrants. This study aimed to investigate the presence and intensity of linguistic ostracism and employee voice behavior and relation among them in Pakistani overseas employees. It may also help to improve the mental health, social life and workplace productivity of Pakistani employees working overseas by learning the coping strategies of ostracism and employee voice behavior. The study employed natural language processing (NLP) and, in particular, the sentiment analysis methodology to analyze the data by using R-Studio. Data was collected from 70 Pakistani employees working outside Pakistan by distributing self-made open-ended questionnaire electronically. Cross sectional research design was used to conduct this research. Lexicon-based sentiment analyses, correlation and regression analyses were done to investigate the nature and strength of relation between LO and EVB. Results suggested negative emotions relevant to linguistic ostracism, employee voice behavior and reduced employee voice behavior in employees. No significant relation was found between LO and EVB. It was also found that linguistic ostracism was not the good predictor of employee voice behavior in Pakistani employees working abroad. Findings of this study would contribute organizations to develop inclusion-focused policies to bring innovation in multilingual workplace settings. This study will also help AI tools designers to design emotion-based tools to improve social interactions among expatriates in multilingual workplace settings.