Behavioral Modeling and Prediction in Social Perception and Computing: A Survey
2023 (English)In: IEEE Transactions on Computational Social Systems, E-ISSN 2329-924X, Vol. 10, no 4, p. 2008-2021Article in journal (Refereed) Published
Abstract [en]
More data are generated through interaction between cyber space, physical space, and social space thanks to mobile network technology, giving birth to the so-called cyber–physical social intelligent ecosystem (C&P-SIE). This survey studies the development of physical social intelligence. First, it classifies and discusses the behavior modeling, learning, and adaptation applications of C&P-SIE from intelligent transportation, healthcare, public service, economy, and social networking. Then, it prospects the application of behavior modeling in the C&P-SIE from the perspectives of information security, data-driven techniques, and modeling learning under cooperative artificial intelligence technologies. The research provides a theoretical basis and new opportunities for the digital and intelligent development of smart cities and social systems. IEEE
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE) Institute of Electrical and Electronics Engineers (IEEE), 2023. Vol. 10, no 4, p. 2008-2021
Keywords [en]
Adaptation models, Artificial intelligence (AI) algorithm, behavior modeling, Computational modeling, cyber–physical social intelligent ecosystem (C&P-SIE), data-driven, Digital Twins, intelligent transportation, Real-time systems, Roads, Social intelligence, Social networking (online), Transportation, Artificial intelligence, Behavioral research, Economic and social effects, Ecosystems, Interactive computer systems, Learning systems, Online systems, Real time systems, Security of data, Social sciences computing, Artificial intelligence algorithms, Behaviour models, Computational modelling, Cyber physicals, Cybe–physical social intelligent ecosystem, Data driven, Real - Time system, Road
National Category
Computer Sciences Information Systems
Identifiers
URN: urn:nbn:se:uu:diva-500268DOI: 10.1109/TCSS.2022.3230211ISI: 000923268300001Scopus ID: 2-s2.0-85146239379OAI: oai:DiVA.org:uu-500268DiVA, id: diva2:1750608
Note
Export Date: 13 April 2023; Article
2023-04-132023-04-132024-12-03Bibliographically approved