Why Employees Leave Russian Companies? Analyzing Online Job Reviews Using Text Mining

Abstract

In this study we analyze topics and sentiments of online job reviews for 989 organizations operating across 12 different knowledge-intensive industries in Russia. Using text mining techniques, such as topic modeling and sentiment analysis, we identify factors of job satisfaction and examine how they differ for former and current employees of Russian organization. The analysis reveals that (1) working arrangements and schedule, (2) working conditions, (3) job content, (4) salary/wage, (5) career development, (6) psychological climate and interpersonal relations with co-workers are the six key topics discussed by employees online in relation to job satisfaction, with the latter -psychological climate and interpersonal relations -being the most widely discussed topic, especially for current employees. Overall, our study suggests that in their decision to leave the company, employees are more likely to tolerate economic factors of job satisfaction (such as salary, career development and working arrangements) rather than socioemotional factors (such as poor relationships with their co-workers and content of work).

The Applications of Sentiment Analysis for Russian Language Texts: Current Challenges and Future Perspectives

“…The next most common data source is product and service reviews, which were analysed in terms of characteristics of reviewers (e.g. [70]), characteristics of products and services (e.g. [71]), and characteristics of merchants (e.g.…”

“…The research group from Saint Petersburg University analysed topics and sentiments of online job reviews for 989 organisations operating across 12 different knowledgeintensive industries in Russia [70]. As a primary source of data, the authors used one of the largest Russian portals of reviews of employers Otrude 17 , operating in Russia.…”