Paper Info
Title
When Emotions Rule Knowledge: A Text-Mining Study Of Emotions In Knowledge Management Research
Abstract
Although emotions play an important role in human behavior and knowledge studies, knowledge management (KM) research considers them from specific angles and, to date, has lacked a comprehensive understanding of the emotions dominating KM. To offer a holistic view, this study investigates the presence of emotions in KM publications by applying a sentiment analysis. The authors present a sentiment dictionary tailored to KM, apply it to KM publications to determine where and how emotions occur, and categorize them on an emotion scale. The considerable amount of positive and negative emotions expressed in KM studies prove their relevance to and dominance in KM. There is high term diversity but also a need to consolidate terms and emotion categories in KM. This study's results provide new insights into the relevance of emotions in KM research, while practitioners can use this method to detect emotion-laden language and successfully implement KM initiatives.
Year
DOI
Venue
2021
10.4018/IJKM.2021070101
INTERNATIONAL JOURNAL OF KNOWLEDGE MANAGEMENT
Keywords
DocType
Volume
Comparison Clouds, Emotion Scales, Emotion Taxonomy, Emotions, Knowledge, Knowledge Management Research, Sentiment Analysis, Sentiment Dictionaries, Text Mining
Journal
17
Issue
ISSN
Citations 
3
1548-0666
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Nora Fteimi132.40
Olivia Hornung200.34
Stefan Smolnik341543.80