Sentiment analysis of write-in comments related to organisational change

Jūratė Čingienė, Dimitri Tcherniak and Benoît Sagot ()
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Jūratė Čingienė: Towers Watson
Dimitri Tcherniak: Towers Watson
Benoît Sagot: Verbatim Analysis - Vera [Paris], ALPAGE - Analyse Linguistique Profonde à Grande Echelle ; Large-scale deep linguistic processing - Inria Paris-Rocquencourt - Inria - Institut National de Recherche en Informatique et en Automatique - UPD7 - Université Paris Diderot - Paris 7

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Abstract: Purpose Sentiment analysis is becoming increasingly popular in social media. In organisational research, however, this technique is underutilised. This paper aims to explore employee and manager sentiments related to recently announced organisational change that were investigated as part of employee opinion survey. Design/Method The data studied here are from an employee opinion survey. Over 5600 employees participated in the survey and 2262 commented on recent organisational transformation. Comments were coded into key themes and their tone was measured using sentiment analysis. The sentiment scores were linked to the themes identified in the comments. Results Mostly negative sentiments were reported regarding the change. Employees were dissatisfied with the lack of information about redundancies, which related to lost in trust employees expressed towards management and general frustration. Differences in sentiments towards specific topics were found in manager and employee populations. Limitations In additional to measuring sentiments, this research would benefit from exploring full range of emotions. Research/Practical Implication This research contributes to employee sentiment research in organisational context. The findings are not surprising- it is expected to find negative tone in employee views on organisational change. This research, however, helps to understand what exact topics drive the negative tone and how this differs by employee and manager populations. Originality/Value Sentiment analysis is quite new in organisational research and this research illustrates one way of how the analysis can be used.

Keywords: Organizational Change and Development; Text Mining; Sentiment Analysis; Natural Language Processing (search for similar items in EconPapers)
Date: 2015-05-20
Note: View the original document on HAL open archive server: https://inria.hal.science/hal-01285621v1
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Published in 17th Congress of the European Association of Work and Organizational Psychology - EAWOP 2015, European Association of Work and Organizational Psychology, May 2015, Oslo, Norway

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