Abstract
The present paper proposes a conceptual ontology to evaluate human factors by modeling their key performance indicators and defining these indicators' explanatory factors, manifestations and diverse corresponding digital footprints. Our methodology incorporates six main human resource constructs: performance, engagement, leadership, workplace dynamics, organizational developmental support, and learning and knowledge creation. Using sentiment analysis, we introduce a potential way to evaluate several components of the proposed human factors ontology. We use the Enron email corpus as a test case, to demonstrate how digital footprints can predict such phenomena. In so doing, we hope to encourage further research applying data mining techniques to allow real time, less costly and more reliable assessments of human factor patterns and trends.