학술논문

A New Perspective for Computational Social Systems: Fuzzy Modeling and Reasoning for Social Computing in CPSS
Document Type
Periodical
Source
IEEE Transactions on Computational Social Systems IEEE Trans. Comput. Soc. Syst. Computational Social Systems, IEEE Transactions on. 11(1):101-116 Feb, 2024
Subject
Computing and Processing
Communication, Networking and Broadcast Technologies
General Topics for Engineers
Social computing
Computational modeling
Fuzzy systems
Uncertainty
Complex systems
Analytical models
Human in the loop
Computational systems
cyber–physical–social systems (CPSSs)
fuzzy paradigm
parallel society
social computing
Language
ISSN
2329-924X
2373-7476
Abstract
The evolution of modern mobile terminals, social networks, and other intelligent services makes everyone become a ubiquitous information perceiver, producer, and propagator. Also known as “social sensor” and “social IoT,” these individuals and communities generate a huge volume of social signals, which has shown prominent value for mining. These unstructured social signals provide a new perspective in the research of complex systems, which makes the traditional cyber–physical system (CPS)-oriented information computing sublimate to the cyber–physical–social system (CPSS)-oriented knowledge computing. However, there still exist great uncertainties, ambiguities, and complexities in modeling behaviors of social individuals or groups. Especially when we apply big-data-driven learning-based models in specific fields and scenarios, the lack of domain expert knowledge and characteristics of system uncertainty severely limits the performance and accuracy of these models. The introduction of fuzzy system modeling integrates data and knowledge in the social computing area, which has shown its unique advantages in solving the above issues and has drawn more attention to this topic. In this article, we conduct a review of recent advances in social computing with fuzzy technologies in CPSS. First, we briefly review the development of social computing, and analyze the characteristics and advantages of social computing through fuzzy methods. Second, we refine core fuzzy system methods for social computing and elaborate on existing fuzzy-technology-empowered social computing methodologies. As in a range of social spaces, we also review and analyze related advances in human-in-the-loop systems. We also reveal the trend of decentralized, autonomous, and organized computing in cyber–physical–social space with fuzzy-based methods and proposed a framework to categorize related studies in CPSS. Finally, we conclude the research trends and hotspots based on current studies, and discuss the challenges for future research directions.