PersoNet: A Novel Framework for Personality Classification-Based Apt Customer Service Agent Selection Article Swipe
Lidia Sandra
,
Harjanto Prabowo
,
Ford Lumban Gaol
,
Sani Muhamad Isa
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/access.2024.3364352
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1109/access.2024.3364352
Personality classification has garnered significant interest in psychology, computational social science, and Machine Learning (ML) due to its wide-ranging applications. This paper presents PersoNet, an innovative framework developed to identify personality types using the Myers-Briggs Type Indicator (MBTI), aimed at enhancing customer service experiences by matching customers with suitable support agents. PersoNet employs a Bidirectional Long Short-Term Memory (BiLSTM) neural network architecture and has achieved an impressive classification accuracy of over 93.98%. Our extensive experiments with the MBTI dataset reveal that the BiLSTM architecture effectively captures both temporal dependencies and semantic subtleties in textual data, contributing to this high level of accuracy. Consequently, PersoNet can accurately select customer service agents who match customer personalities, achieving a Customer Satisfaction Rate (CSR) of over 97.82%–a notable improvement of 20.25% in CSR based on our experimental data. These results establish PersoNet as a cutting-edge tool in personality classification, surpassing existing methods in both accuracy and computational efficiency and markedly enhancing customer service quality.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2024.3364352
- https://ieeexplore.ieee.org/ielx7/6287639/6514899/10430165.pdf
- OA Status
- gold
- Cited By
- 4
- References
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- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391661554
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391661554Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2024.3364352Digital Object Identifier
- Title
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PersoNet: A Novel Framework for Personality Classification-Based Apt Customer Service Agent SelectionWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-01-01Full publication date if available
- Authors
-
Lidia Sandra, Harjanto Prabowo, Ford Lumban Gaol, Sani Muhamad IsaList of authors in order
- Landing page
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https://doi.org/10.1109/access.2024.3364352Publisher landing page
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https://ieeexplore.ieee.org/ielx7/6287639/6514899/10430165.pdfDirect link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/6287639/6514899/10430165.pdfDirect OA link when available
- Concepts
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Computer science, Personality, Personality psychology, Matching (statistics), Artificial intelligence, Service (business), Customer satisfaction, Service quality, Machine learning, Customer service, Data mining, Knowledge management, Marketing, Psychology, Social psychology, Mathematics, Business, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 2Per-year citation counts (last 5 years)
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51Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_date | 2024-01-01 |
| publication_year | 2024 |
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