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Sentiment Analysis in Organizational Work: Toward an Ontology of People Analytics

Gelbard, Roy, Ramon-Gonen, Roni, Carmeli, Abraham, Bittmann, Ran M. and Talyansky, Roman (2018) Sentiment Analysis in Organizational Work: Toward an Ontology of People Analytics Expert Systems, 35 (5), e12289.

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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.

Item Type: Article
Divisions : Faculty of Arts and Social Sciences > Surrey Business School
Authors :
NameEmailORCID
Gelbard, Roy
Ramon-Gonen, Roni
Carmeli, Abrahama.carmeli@surrey.ac.uk
Bittmann, Ran M.
Talyansky, Roman
Date : 25 May 2018
DOI : 10.1111/exsy.12289
Copyright Disclaimer : This is the peer reviewed version of an article which has been published in final form at https://onlinelibrary.wiley.com/doi/abs/10.1111/exsy.12289.This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions
Uncontrolled Keywords : Human resource management; Key performance indicators; Sentiment analysis; People analytics; Workforce Analytics.
Additional Information : Special Issue: New trends and innovations in intelligent distributed computing
Depositing User : Clive Harris
Date Deposited : 15 May 2018 15:16
Last Modified : 26 May 2019 02:08
URI: http://epubs.surrey.ac.uk/id/eprint/846414

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