Detecting Workplace Hubris: A Machine Learning Approach to Narcissism Identification. The Case of the Healthcare Industry in the Emerging Markets
Detecting Workplace Hubris: A Machine Learning Approach to Narcissism Identification. The Case of the Healthcare Industry in the Emerging Markets

Summary/Abstract: Despite the extensive research on narcissism and its origin, the world of health practice, risk factors, as well as the case in a developing country like Morocco, is a new untapped area. This work explores uncharted territory as it attempts to replace the existing social behavior prediction tools with different machine learning models that promise the best approach to narcissist behavior prediction by identifying psychological features characteristic of narcissist personalities. Among different machine learning models used in this study, Support Vector Machine (SVM) shows the highest metrics with an accuracy of 0.910, precision of 0.890, and recall of 0.880. SVM reveals that vanity, self-sufficiency, authority, and exhibitionism are the best predictors of narcissism in organizational settings.

• Details
• Contents