Transforming Leadership Assessment Using Natural Language Processing

Scott Tonidandel · Betsy H. Albritton

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Computational and Text Analysis Methods Sentiment Analysis and Opinion Mining AI and HR Technologies

Abstract

Abstract Advancements in computer science, specifically natural language processing (NLP), offer innovative opportunities to transform leadership assessment. This chapter first defines NLP and describes the many analytic techniques within NLP, including computer-aided text analysis, supervised machine learning, and unsupervised machine learning. For each technique, tangible examples of their use in leadership assessment research are provided. The chapter also advises scientists and practitioners interested in NLP on unique methodological considerations for its use in leadership assessment and provides resources that would be most beneficial. The chapter concludes by recommending future applications of NLP in assessing leaders, including suggestions of evaluative NLP models of leader behaviors that can offer real-time feedback to leaders.

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2019HISTORIAE, History of Socio-Cultural Transformation as Linguistic Data Science. A Humanities Use Case 2010Signaling Theory: A Review and Assessment 2012Linguistic Inquiry and Word Count (LIWC)2018quanteda: An R package for the quantitative analysis of textual data 2020Text Preprocessing for Text Mining in Organizational Research: Review and Recommendations 2020Women’s leadership is associated with fewer deaths during the COVID-19 crisis: Quantitative and qualitative analyses of United States governors.2018The nature of followership: Evolutionary analysis and review 2018A Review of Best Practice Recommendations for Text Analysis in R (and a User-Friendly App)

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