A New Perspective for Computational Social Systems: Fuzzy Modeling and Reasoning for Social Computing in CPSS

Wang, Tan; Zhu, Yifan; Ye, Peijun; Gong, Weichao; Lü, Hao; Mo, Hong; Wang, Fei-Yue

doi:10.1109/tcss.2022.3197421

Cited by 11 publications

(15 citation statements)

References 165 publications

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“…Using the same dataset, the proposed PersoNet performs much better than this method. The Fuzzy-Logicbased approach of T. Wang et al [21] uses the Mayers-Briggs Type Indicator (MBTI) dataset to model digital personality. H. Lin et al [22] used the Gray Wolf Optimizer (GWO) to select features from high-dimensional psycho-linguistics characteristics to classify personalities.…”

Section: K Karunarathna Et Al Conducted a Study On Personality Classi...mentioning

confidence: 99%

PersoNet: A Novel Framework for Personality Classification-Based Apt Customer Service Agent Selection

Sandra,

Prabowo,

Gaol

et al. 2024

IEEE Access

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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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Section: K Karunarathna Et Al Conducted a Study On Personality Classi...mentioning

confidence: 99%

PersoNet: A Novel Framework for Personality Classification-Based Apt Customer Service Agent Selection

Sandra,

Prabowo,

Gaol

et al. 2024

IEEE Access

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“…• Computational Challenges: The high computational costs of running sophisticated AI models like ChatGPT in realtime environments, such as those required for intelligent vehicles, pose significant challenges. Discussions might delve into optimizing computational resources and developing more efficient AI models that can operate within the constraints of vehicular technology [76].…”

Section: Computer Science and Itmentioning

confidence: 99%

“…• Ethical and Practical Considerations: Implementing AI in sensitive applications such as vehicles brings ethical and practical considerations to the forefront. Discussions might touch on the responsibility for AI-driven decisions, privacy concerns related to data collection and usage, and the integrity of the AI systems in terms of providing unbiased and accurate information [76].…”

Section: Computer Science and Itmentioning

confidence: 99%

“…• The advent of language models like ChatGPT has broadened the computational landscape, particularly in social systems and AI linguistic frameworks. Wang et al delve into the utilization of ChatGPT within computational social systems, examining its transition from simple conversational applications to more complex, human-oriented operating systems [76]. Their work likely discusses the integration of AI in social contexts, emphasizing the need for systems that not only process information but also understand and adapt to human nuances, potentially transforming user interaction with technology.…”

Section: Computer Science and Itmentioning

confidence: 99%

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Global Insights and the Impact of Generative AI-ChatGPT on Multidisciplinary: A Systematic Review and Bibliometric Analysis

Khan,

Koubaa

et al. 2024

Preprint

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“…While previous research has explored various factors that contribute to job satisfaction and perceived workload among employees, limited attention has been given to understanding the influence of personality typology specifically within the context of subway train drivers. Personality traits can significantly impact individuals’ behaviors, attitudes, and perceptions, and thus understanding the interplay between personality types and job-related outcomes is of paramount importance ( Hitka and Stípalová, 2011 ; Chang et al, 2021 ; Wang T. et al, 2023 ).…”

Section: Introductionmentioning

confidence: 99%

Job satisfaction and perceived workload in the context of personality typology among subway train drivers

Gottwald,

Lejsková

2023

Front. Psychol.

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Job satisfaction is a highly relevant topic across all sectors of the national economy worldwide. A contented employee significantly enhances a company’s performance compared to a dissatisfied one. Simultaneously, a contented employee increases the human capital value of the company, which has a substantial impact on its overall value. However, employee satisfaction is not a static state; it can be influenced by various factors, one of which is perceived workload resulting from the nature of the job. The aim of this article is to investigate whether there is a demonstrable impact of perceived workload on employee satisfaction. This relationship is examined within the context of subway train drivers in the Czech Republic. In exploring this relationship, we also delve into the psychological factor of whether there is a connection between perceived workload and the satisfaction of subway train drivers based on their personality types according to the MBTI test. These dependencies are assessed through correlation analysis using a comprehensive dataset obtained. In the course of the research, data were collected from the entire basic sample of respondents, namely from 654 subway train drivers. The results confirmed the existing influence of perceived workload on employee satisfaction and, concurrently, the influence of perceived workload on employee satisfaction based on the personality typology determined by the MBTI test. These findings are undoubtedly beneficial for the management of transportation companies, particularly those involved in passenger transportation, specifically in the provision of subway services.

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A New Perspective for Computational Social Systems: Fuzzy Modeling and Reasoning for Social Computing in CPSS

Cited by 11 publications

References 165 publications

PersoNet: A Novel Framework for Personality Classification-Based Apt Customer Service Agent Selection

PersoNet: A Novel Framework for Personality Classification-Based Apt Customer Service Agent Selection

Global Insights and the Impact of Generative AI-ChatGPT on Multidisciplinary: A Systematic Review and Bibliometric Analysis

Job satisfaction and perceived workload in the context of personality typology among subway train drivers

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