{
  "abstract": "Portable power banks, as a cornerstone of China’s mobile and shared energy market, are closely integrated into daily life and work. The recent, ongoing exposure of safety incidents has led to stricter control measures in specific industries and regions, and even to the revision of relevant administrative management standards, posing a significant challenge to an industry with over a decade of rapid growth. The expectations of the public and government administrative management for product safety, reliability, and service quality have risen rapidly. Therefore, real-time public opinion monitoring is vital for supporting technological innovation, safety governance, and the sustainable development of the industry. However, traditional opinion mining methods struggle to interpret short, noisy, and user-generated data and often lack generalizable semantic understanding. This study therefore develops an LLM-driven framework that first clusters LLM-augmented multi-view representations via graph-based consensus spectral clustering to discover latent topics, followed by multi-label topic assignment and aspect-based sentiment analysis through multi-LLM consensus voting. A total of 47,023 public comments were collected from China’s leading social media platforms, yielding 12 key discussion topics covering electrical safety, charging performance, device durability, shared rental experiences, and emerging magnetic attachment design. The results show that there are strong negative views on electrical safety (86.1%) and the convenience of shared rental services (78.4%), while the views on magnetic connection innovation are mainly positive (76.6%). The topic-event correlation analysis further indicates that opinion fluctuations are closely related to pricing disputes and security-related events. This study demonstrates the effectiveness of LLM-enhanced semantic modeling in public opinion monitoring in the consumer electronics energy field. The results offer reference value for emerging industry market norms under discussion, while the proposed framework can further support the sustainability of portable energy market development by guiding product optimization, risk early warning, and data-informed regulatory strategies.",
  "abstract_shown": true,
  "affiliations": [
    "College of Artificial Intelligence, Chengdu University of Information Technology, Chengdu, China",
    "School of Software Engineering, Chengdu University of Information Technology, Chengdu, China",
    "School of Computing and Artificial Intelligence, Southwestern University of Finance and Economics, Chengdu, China",
    "School of Management Science and Engineering, Southwestern University of Finance and Economics, Chengdu, China"
  ],
  "article_type": "Research Article",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yun Zhang"
    },
    {
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        1
      ],
      "name": "Weikang Xie"
    },
    {
      "affs": [
        2
      ],
      "name": "Xiao Li"
    },
    {
      "affs": [
        3
      ],
      "name": "Wei Liao"
    },
    {
      "name": "Tao Shu"
    },
    {
      "name": "Jixian Zhou"
    },
    {
      "name": "Jun Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/e4czt5whm9rww.bib",
  "cited_by": 0,
  "doi": "10.1371/journal.pone.0357018",
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  "id": "e4czt5whm9rww",
  "issns": [
    "1932-6203"
  ],
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  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "1702|Sentiment Analysis and Opinion Mining"
    ],
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      "plos",
      "/Biology and life sciences/Neuroscience/Cognitive science/Cognitive psychology/Language"
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      "plos",
      "/Biology and life sciences/Psychology/Psychological attitudes"
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      "plos",
      "/Computer and information sciences/Data management/Data mining"
    ],
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      "plos",
      "/Computer and information sciences/Network analysis/Social networks/Social media"
    ],
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      "/Medicine and health sciences/Epidemiology/Medical risk factors"
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      "/Research and analysis methods/Mathematical and statistical techniques/Cluster analysis/Spectral clustering"
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      "/Social sciences/Linguistics/Semantics"
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      "/Social sciences/Psychology/Cognitive psychology/Language"
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      "/Social sciences/Psychology/Emotions"
    ],
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      "plos",
      "/Social sciences/Psychology/Psychological attitudes"
    ],
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      "plos",
      "/Social sciences/Sociology/Communications/Social communication/Social media"
    ],
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      "plos",
      "/Social sciences/Sociology/Social networks/Social media"
    ]
  ],
  "openalex": "W7213403122",
  "pdf_url": "https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0357018&type=printable",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-16",
  "publisher": "Public Library of Science",
  "ris": "https://research.draconitic.com/paper/e4czt5whm9rww.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:49Z",
      "native_id": "10.1371/journal.pone.0357018",
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  "subjects": [
    {
      "field": "biology",
      "origin": "plos:neuroscience",
      "subfield": "neuroscience"
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      "origin": "plos:epidemiology",
      "subfield": "epidemiology-public-health"
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  "title": "Large language model enhanced public opinion monitoring for China’s portable energy market: A data driven analysis of social media comments",
  "title_text": "Large language model enhanced public opinion monitoring for China’s portable energy market: A data driven analysis of social media comments",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:49Z",
  "url": "https://research.draconitic.com/paper/e4czt5whm9rww",
  "venue": "PLOS One",
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}