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Nuclear Pollution or Safe Discharge

Topic Evolution and Cognitive Analysis on Fukushima's Treated Radioactive Water

Bibliographic Data

ID22107015
AuthorsXin Liu (0000-0001-5207-1685, Institute of Software), Ziliang Chen (0000-0003-0105-728X, Institute of Software), Fei‐yue Wang (0000-0001-9185-3989, Beijing Academy of Artificial Intelligence), Dawei Yang (0000-0002-1868-2746, Institute of Software), Rui Qin (0000-0003-3473-2173, Chinese Academy of Sciences), Mingjiang Pang (0009-0008-3152-1198, Institute of Software), Qinghua Ni (0009-0000-6100-5946, Macau University of Science and Technology), Huiquan Gao (0009-0001-1220-9480, Institute of Software)
Year2024
Volume11
Issue6
Pages7338-7347
Publication date2024-12-01
Open AccessYes
TypeARTICLE
VenueIEEE Transactions on Computational Social Systems (JOURNAL)
Journal identifiersISSN: 2329-924X • E-ISSN: 2373-7476
PublisherInstitute of Electrical and Electronics Engineers (IEEE) (PUBLISHER)
DOI10.1109/tcss.2024.3406700
OpenAlexW4399727999
LanguageEN
Citations received1
References cited25

In the context of the Societies 5.0, a series of discussions on the emerging Fukushima treated radioactive water (FTRW) event was carried out, which has an impact on sustainable development in multiple fields including the economy, culture, and society. In order to comprehensively understand emerging topics and their evolution, explore the impact of people's cognition on their participation, and focus on people's attitudes and public participation in the FTRW event, we propose an evolution analysis framework (EAF) to analyze the massive multilingual comments and news collected from social media platforms in several countries. We design a multilingual topic extraction model (XLM-topic) to detect the patterns of topics and analyze their evolution. Potential relations between the FTRW event's elements are explored by relational reasoning based on a knowledge graph, which is established by entities and relations extracted from comments and news. Moreover, we predict the public attitudes and participation toward the FTRW event by utilizing our custom-designed public opinion cellular automata (POCA). The proposed POCA simulates the information dissemination, cognitive changes, and topic evolution among social groups in virtual spaces. It collaborates with XLM-topic to analyze trends in both physical and virtual spaces. Analysis results indicate that participants in different regions and countries have different attitudes and reactions toward the FTRW event, and the public's cognition on this event will interact with itself. Our study is conducive to promoting the integration and interaction of virtual space and physical space in the context of Societies 5.0, providing decision-making support for building a more harmonious and stable social environment

Biology · Radioactive waste · Waste management · Water pollution · Chemistry · Engineering · Environmental Science · Radioactive contamination and transfer · Ecology · Environmental Chemistry · Pollution

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Citations per year1
Citation span2025 - 2025 (1)
Highly citedNo

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