<?xml version="1.0" encoding="UTF-8"?>
<article xmlns:xlink="http://www.w3.org/1999/xlink" xml:lang="en" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
  <front>
    <journal-meta>
      <journal-id journal-id-type="ojs">JDC</journal-id>
      <journal-title-group>
        <journal-title xml:lang="en">Journal of Discovery Core</journal-title>
        <abbrev-journal-title xml:lang="en">JDC</abbrev-journal-title>
      </journal-title-group>
      <publisher>
        <publisher-name>Digital Intelligence Press</publisher-name>
        <publisher-loc>Hong Kong<country>HK</country><uri>https://dipscie.com/index.php/JDC/index</uri></publisher-loc>
      </publisher>
      <issn pub-type="epub">3135-7687</issn>
      <self-uri xlink:href="https://dipscie.com/index.php/JDC"/>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="publisher-id">58</article-id>
      <article-categories>
        <subj-group xml:lang="en" subj-group-type="heading">
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title xml:lang="en">&lt;bold&gt;Simulation Study on Digital Divide Propagation Path of Elderly Medical Treatment Based on Graph Neural Network and Public Social Network Data&lt;/bold&gt;</article-title>
      </title-group>
      <contrib-group content-type="author">
        <contrib>
          <name-alternatives>
            <name name-style="western" specific-use="primary">
              <surname>Yang</surname>
              <given-names>Linna</given-names>
            </name>
          </name-alternatives>
          <email>linayang827@outlook.com</email>
          <xref ref-type="aff" rid="aff-1"/>
        </contrib>
      </contrib-group>
      <aff id="aff-1">
        <institution content-type="orgname">School of Economics and Management, Lanzhou Institute of Technology, Lanzhou, Gansu, China</institution>
      </aff>
      <pub-date date-type="pub" publication-format="epub">
        <day>01</day>
        <month>10</month>
        <year>2026</year>
      </pub-date>
      <fpage>38</fpage>
      <lpage>79</lpage>
      <pub-history>
        <event event-type="received">
          <event-desc>Received: <date date-type="received" iso-8601-date="2026-07-24T06:08:31+00:00"><day>24</day><month>7</month><year>2026</year></date></event-desc>
        </event>
      </pub-history>
      <permissions>
        <copyright-statement>Copyright (c) 2026 Linna Yang (Author)</copyright-statement>
        <copyright-year>2026</copyright-year>
        <copyright-holder>Linna Yang (Author)</copyright-holder>
        <license xlink:href="https://creativecommons.org/licenses/by/4.0">
          <license-p>&lt;a rel="license" href="https://creativecommons.org/licenses/by/4.0/"&gt;&lt;img alt="Creative Commons License" src="//i.creativecommons.org/l/by/4.0/88x31.png" /&gt;&lt;/a&gt;&lt;p&gt;This work is licensed under a &lt;a rel="license" href="https://creativecommons.org/licenses/by/4.0/"&gt;Creative Commons Attribution 4.0 International License&lt;/a&gt;.&lt;/p&gt;</license-p>
        </license>
      </permissions>
      <self-uri xlink:href="https://dipscie.com/index.php/JDC/article/view/10.67541_jdf2609"/>
      <kwd-group xml:lang="en">
        <kwd>Digital divided in medical treatment for the elderly; Graph neural network; Propagation path simulation; Heterogeneous social networks; Optimization of intervention strategy</kwd>
      </kwd-group>
      <counts>
        <page-count count="42"/>
      </counts>
      <custom-meta-group/>
    </article-meta>
  </front>
  <body/>
  <back>
    <ref-list>
      <ref id="R1">
        <mixed-citation>[1] Erku, D., Khatri, R., Endalamaw, A., Wolka, E., Nigatu, F., Zewdie, A., &amp; Assefa, Y. (2023). Digital health interventions to improve access to and quality of primary health care services: a scoping review. International journal of environmental research and public health, 20(19), 6854. https://doi.org/10.3390/ijerph20196854</mixed-citation>
      </ref>
      <ref id="R2">
        <mixed-citation>[2] Paul, S., Riffat, M., Yasir, A., Mahim, M. N., Sharnali, B. Y., Naheen, I. T., ... &amp; Kulkarni, A. (2021). Industry 4.0 applications for medical/healthcare services. Journal of Sensor and Actuator Networks, 10(3), 43. https://doi.org/10.3390/jsan10030043</mixed-citation>
      </ref>
      <ref id="R3">
        <mixed-citation>[3] Hermes, S., Riasanow, T., Clemons, E. K., Böhm, M., &amp; Krcmar, H. (2020). The digital transformation of the healthcare industry: exploring the rise of emerging platform ecosystems and their influence on the role of patients. Business Research, 13(3), 1033-1069. https://doi.org/10.1007/s40685-020-00125-x</mixed-citation>
      </ref>
      <ref id="R4">
        <mixed-citation>[4] Li, H., Li, Q., Yang, Z., &amp; Shangguan, X. (2026). Digital technology-enabled public services and rural residents’ subjective wellbeing: synergies and pathways in China. Frontiers in Sustainable Food Systems, 10, 1718922. https://doi.org/10.3389/fsufs.2026.1718922</mixed-citation>
      </ref>
      <ref id="R5">
        <mixed-citation>[5] Zhao, Y., Zhang, T., Dasgupta, R. K., &amp; Xia, R. (2023). Narrowing the age‐based digital divide: Developing digital capability through social activities. Information Systems Journal, 33(2), 268-298. https://doi.org/10.1111/isj.12400</mixed-citation>
      </ref>
      <ref id="R6">
        <mixed-citation>[6] Cui, Y., Bao, H., Wen, K., &amp; Wen, H. (2025). Bridging the digital health divide: digital endowment, informal social participation, and health inequality among older adults. BMC Health Services Research, 26(1), 99. https://doi.org/10.1186/s12913-025-13872-6</mixed-citation>
      </ref>
      <ref id="R7">
        <mixed-citation>[7] Faye, R., &amp; Ravneberg, B. E. (2024, May). Making vulnerable groups able to connect socially and digitally—Opportunities and pitfalls. In Frontiers in education (Vol. 9, p. 1346721). Frontiers Media SA. https://doi.org/10.3389/feduc.2024.1346721</mixed-citation>
      </ref>
      <ref id="R8">
        <mixed-citation>[8] Coles-Kemp, L., Robinson, N., &amp; Heath, C. P. (2022). Protecting the vulnerable: Dimensions of assisted digital access. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2), 1-26. https://doi.org/10.1145/3555647</mixed-citation>
      </ref>
      <ref id="R9">
        <mixed-citation>[9] Martin, F., Ceviker, E., &amp; Gezer, T. (2026). From digital divide to digital equity: Systematic review of two decades of research on educational digital divide factors, dimensions, and interventions. Journal of Research on Technology in Education, 58(2), 396-421. https://doi.org/10.1080/15391523.2024.2425442</mixed-citation>
      </ref>
      <ref id="R10">
        <mixed-citation>[10] Aruleba, K., &amp; Jere, N. (2022). Exploring digital transforming challenges in rural areas of South Africa through a systematic review of empirical studies. Scientific African, 16, e01190. https://doi.org/10.1016/j.sciaf.2022.e01190</mixed-citation>
      </ref>
      <ref id="R11">
        <mixed-citation>[11] Zhou, L., Lin, J., Li, Y., &amp; Zhang, Z. (2020). Innovation diffusion of mobile applications in social networks: A multi-agent system. Sustainability, 12(7), 2884. https://doi.org/10.3390/su12072884</mixed-citation>
      </ref>
      <ref id="R12">
        <mixed-citation>[12] Zareer, M., &amp; Selmic, R. R. (2025). A survey on opinion dynamics in social media networks: Analysis, simulation, and control. IEEE Transactions on Computational Social Systems. https://doi.org/10.1109/TCSS.2025.3622498</mixed-citation>
      </ref>
      <ref id="R13">
        <mixed-citation>[13] Fan, R., Yang, L., Liu, D., &amp; Hu, W. (2026). Value allocation mechanism for multi-agent data sharing in digital innovation network: Agent-based modeling. Expert Systems with Applications, 299, 130124. https://doi.org/10.1016/j.eswa.2025.130124</mixed-citation>
      </ref>
      <ref id="R14">
        <mixed-citation>[14] Tai, Y., He, H., Zhang, W., Yang, H., Wu, X., &amp; Wang, Y. (2023). Predicting information diffusion using the inter-and intra-path of influence transitivity. Information Sciences, 651, 119705. https://doi.org/10.1016/j.ins.2023.119705</mixed-citation>
      </ref>
      <ref id="R15">
        <mixed-citation>[15] Zheng, Y., Yi, L., &amp; Wei, Z. (2025). A survey of dynamic graph neural networks. Frontiers of Computer Science, 19(6), 196323. https://doi.org/10.1007/s11704-024-3853-2</mixed-citation>
      </ref>
      <ref id="R16">
        <mixed-citation>[16] Feng, Z., Wang, R., Wang, T., Song, M., Wu, S., &amp; He, S. (2025). A comprehensive survey of dynamic graph neural networks: Models, frameworks, benchmarks, experiments and challenges. IEEE Transactions on Knowledge and Data Engineering. https://doi.org/10.1109/TKDE.2025.3621291</mixed-citation>
      </ref>
      <ref id="R17">
        <mixed-citation>[17] Gondal, N. (2023). Diffusion of innovations through social networks: Determinants and implications. Sociology Compass, 17(5), e13084. https://doi.org/10.1111/soc4.13084</mixed-citation>
      </ref>
      <ref id="R18">
        <mixed-citation>[18] Xiang, S., Ling, H., &amp; Wu, M. (2026). Cross-Modal Alignment and Rectified Flow-Based Latent Representation Synthesis for Enhanced Speech-Driven Alzheimer’s Disease Detection. Bioengineering, 13(3), 370. https://doi.org/10.3390/bioengineering13030370</mixed-citation>
      </ref>
      <ref id="R19">
        <mixed-citation>[19] Zhuo, S., Fang, J., Lin, H., Li, N., Zhou, Y., Zhang, S., ... &amp; Huang, S. (2026). EdgeGFL: rethinking edge information in graph feature preference learning. International Journal of Machine Learning and Cybernetics, 17(5), 240. https://doi.org/10.1007/s13042-026-03060-1</mixed-citation>
      </ref>
      <ref id="R20">
        <mixed-citation>[20] You, X., Zhang, M., Ma, Y., Tan, J., &amp; Liu, Z. (2023). Impact of higher-order interactions and individual emotional heterogeneity on information-disease coupled dynamics in multiplex networks. Chaos, Solitons &amp; Fractals, 177, 114186. https://doi.org/10.1016/j.chaos.2023.114186</mixed-citation>
      </ref>
      <ref id="R21">
        <mixed-citation>[21] Gong, Z., Shao, J., Rahman, N., Su, L. Y. F., &amp; Wang, Y. C. (2026). Modality matters: comparing the persuasiveness of text-and voice-based conversational agents and non-interactive messages in health communication. Internet Research, 1-25. https://doi.org/10.1108/INTR-07-2025-1004</mixed-citation>
      </ref>
      <ref id="R22">
        <mixed-citation>[22] Cui, S., &amp; Zhu, X. (2024). The information propagation mechanism of individual heterogeneous adoption behavior under the heterogeneous network. Frontiers in Physics, 12, 1404464. https://doi.org/10.3389/fphy.2024.1404464</mixed-citation>
      </ref>
      <ref id="R23">
        <mixed-citation>[23] Yang, Y. (2025, July). Research on Evaluation Model of Urban-rural Integration Development Based on Deep Learning. In Proceedings of the 2025 3rd International Conference on Educational Knowledge and Informatization (pp. 406-410). https://doi.org/10.1145/3765325.3765393</mixed-citation>
      </ref>
      <ref id="R24">
        <mixed-citation>[24] Ao, X., Gong, Y., &amp; He, A. (2025). A review of time series prediction models based on deep learning. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3602791</mixed-citation>
      </ref>
      <ref id="R25">
        <mixed-citation>[25] Yu, Y., &amp; Huo, L. A. (2025). Effects of official information diffusion and rumor-related behavior adoption on epidemic transmission in multiplex networks. Information Sciences, 689, 121414. https://doi.org/10.1016/j.ins.2024.121414</mixed-citation>
      </ref>
      <ref id="R26">
        <mixed-citation>[26] Liu, Y., Zhang, P., Shi, L., &amp; Gong, J. (2023). A survey of information dissemination model, datasets, and insight. Mathematics, 11(17), 3707. https://doi.org/10.3390/math11173707</mixed-citation>
      </ref>
      <ref id="R27">
        <mixed-citation>[27] Theodorakopoulos, L., Theodoropoulou, A., &amp; Klavdianos, C. (2025). Interactive viral marketing through big data analytics, influencer networks, AI integration, and ethical dimensions. Journal of Theoretical and Applied Electronic Commerce Research, 20(2), 115. https://doi.org/10.3390/jtaer20020115</mixed-citation>
      </ref>
      <ref id="R28">
        <mixed-citation>[28] Yue, Z., Witzig, C. R., Jorde, D., &amp; Jacobsen, H. A. (2020, November). Bert4nilm: A bidirectional transformer model for non-intrusive load monitoring. In Proceedings of the 5th international workshop on non-intrusive load monitoring (pp. 89-93). https://doi.org/10.1145/3427771.3429390</mixed-citation>
      </ref>
      <ref id="R29">
        <mixed-citation>[29] Liao, T., Ta, X., Xu, Y., Han, L., Sun, L., &amp; Lv, W. (2025). SimPRL: a simple contrastive learning for path representation learning by joint GPS trajectories and road paths. IEEE Transactions on Intelligent Transportation Systems, 27(1), 400-413. https://doi.org/10.1109/TITS.2025.3629800</mixed-citation>
      </ref>
      <ref id="R30">
        <mixed-citation>[30] Yang, C., Xiao, Y., Zhang, Y., Sun, Y., &amp; Han, J. (2020). Heterogeneous network representation learning: A unified framework with survey and benchmark. IEEE Transactions on Knowledge and Data Engineering, 34(10), 4854-4873. https://doi.org/10.1109/TKDE.2020.3045924</mixed-citation>
      </ref>
    </ref-list>
  </back>
</article>