Jointly Predicting Job Performance, Personality, Cognitive Ability, Affect, and Well-Being

Abstract

Assessment of job performance, personalized health and psychometric measures are domains where data-driven and ubiquitous computing exhibits the potential of a profound impact in the near future. Existing techniques use data extracted from questionnaires, sensors (wearable, computer, etc.), or other traits, to assess well-being and cognitive attributes of individuals. However, these techniques can neither predict individuals wellbeing and psychological traits in a global manner nor consider the challenges associated to processing the data available, that is incomplete and noisy. In this paper, we create a benchmark for predictive analysis of individuals from a perspective that integrates: physical and physiological behavior, psychological states and traits, and job performance. We design data mining techniques as benchmark and uses real noisy and incomplete data derived from wearable sensors to predict 19 constructs based on 12 standardized well-validated tests. The study included 757 participants who were knowledge workers in organizations across the USA with varied work roles. We developed a data mining framework to extract the meaningful predictors for each of the 19 variables under consideration. Our model is the first benchmark that combines these various instrument-derived variables in a single framework to understand people's behavior by leveraging real uncurated data from wearable, mobile, and social media sources. We verify our approach experimentally using the data obtained from our longitudinal study. The results show that our framework is consistently reliable and capable of predicting the variables under study better than the baselines when prediction is restricted to the noisy/incomplete data.

Short video users’ personality traits and social sharing motivation

“…Early research on the five-factor model and user behaviour focused only on a limited number of aspects, such as personality and interpersonal relationships, personality and purchase propensity, and personality and career choice, with extraversion and conscientiousness being the most frequently studied personality traits (Forret and Dougherty, 2001;Robles-Granda et al, 2020). Due to the development of online technologies, especially the emergence of social networks, interpersonal communication has changed.…”