Sentiment analysis in organizational work: Towards an ontology of people analytics

Roy Gelbard*, Roni Ramon-Gonen, Abraham Carmeli, Ran M. Bittmann, Roman Talyansky

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The present paper proposes a conceptual ontology to evaluate human factors by modelling their key performance indicators and defining these indicators' explanatory factors, manifestations, and diverse corresponding digital footprints. Our methodology incorporates 6 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.

Original languageEnglish
Article numbere12289
JournalExpert Systems
Volume35
Issue number5
DOIs
StatePublished - Oct 2018

Keywords

  • human resource management
  • key performance indicators
  • people analytics
  • sentiment analysis
  • workforce analytics

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