Applications of text mining in services management: A systematic literature review
Применение текстового анализа в управлении услугами: систематический обзор литературы
2021-02-26
SCID: 54.1/mee58a6r
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competitive intelligencefake content detectionmarket analysisnatural language processingrisk managementsentiment analysisservices managementsocial media analysissystematic literature reviewtext miningtopic modelingvisualization tools for text mining
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Abstract (AI)
The importance of text mining is increasing in services management as the access to big data is increasing across digital platforms enabling such services. This study adopts a systematic literature review on the application of text mining in services management. First, we analyzed the literature on which has used text mining methods like Sentiment Analysis, Topic Modeling, and Natural language Processing (NLP) in reputed business management journals. Further, we applied visualization tools for text mining and the topic association to understand the dominant themes and relationships. The analysis highlighted that social media analysis, market analysis, competitive intelligence are the most dominant themes while other themes like risk management and fake content detection are also explored. Further, based on the analysis, future research agenda in the field of text mining in services management has been indicated.
Key Findings
1
A systematic literature review identified Sentiment Analysis, Topic Modeling, and NLP as commonly used methods in business management journals.
2
Other explored themes include risk management and fake content detection.
3
Social media analysis, market analysis, and competitive intelligence are the most dominant themes in text-mining-for-services-management research.
4
Text mining use in services management is growing due to increased access to big data across digital platforms.
5
The study proposes a future research agenda for text mining applications in services management based on the review.
6
Visualization tools and topic association analyses reveal dominant themes and relationships in the literature.
Research Object
Applications of text mining methods (e.g., Sentiment Analysis, Topic Modeling, NLP) in services management literature
Research Subject
The thematic use, dominant themes (social media analysis, market analysis, competitive intelligence, risk management, fake content detection), and topic associations revealed by text-mining studies in services management, derived via systematic literature review and visualization
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2021-02-26
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