IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i18p11650-d916833.html
   My bibliography  Save this article

The Changing Tendency and Association Analysis of Intelligent Coal Mines in China: A Policy Text Mining Study

Author

Listed:
  • Xiaofang Wo

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

  • Guichen Li

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

  • Yuantian Sun

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China
    State Key Laboratory of Green and Low-Carbon Development of Tar-rich Coal in Western China, Xi’an University of Science and Technology, Xi’an 710054, China)

  • Jinghua Li

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

  • Sen Yang

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

  • Haoran Hao

    (School of Mines, China University of Mining and Technology, Xuzhou 221116, China
    Key Laboratory of Deep Coal Resource Mining of the Ministry of Education, China University of Mining and Technology, Xuzhou 221116, China)

Abstract

The intellectualization of coal mines provides core technical support for the high-quality development of the coal industry. Intelligent texts, especially intelligent policy documents, play an extremely important role in analyzing the trend of intelligent policies in coal mines. This paper collects more than 50 central and local intelligent coal mine policy texts from recent years. The method of text analysis is a tool used for text mining, and semantic networks are generated; it reflects that the policy mainly focuses on promoting large-scale equipment and platform integration, to promote the overall goal of safe, efficient, and intelligent development of coal mining. By analyzing the high-frequency words of the policy from 2016 to 2022, it reflects that the policy trend mainly goes through the following three stages: firstly, eliminate backward enterprises, encourage coal mine automation and mechanization; then, standardize the basic concept of coal mine intellectualization, carry out the transformation of coal mine intellectualization; and the third stage is to promote the application of key technologies of intellectualization, build intelligent demonstration coal mines and reach the acceptance stage, and promote the further development trend of coal mine intellectualization.

Suggested Citation

  • Xiaofang Wo & Guichen Li & Yuantian Sun & Jinghua Li & Sen Yang & Haoran Hao, 2022. "The Changing Tendency and Association Analysis of Intelligent Coal Mines in China: A Policy Text Mining Study," Sustainability, MDPI, vol. 14(18), pages 1-14, September.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11650-:d:916833
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/18/11650/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/18/11650/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ze Wang & Huajiao Li & Renwu Tang, 2019. "Network analysis of coal mine hazards based on text mining and link prediction," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 30(07), pages 1-22, July.
    2. Li, Huajiao & An, Haizhong & Wang, Yue & Huang, Jiachen & Gao, Xiangyun, 2016. "Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 657-669.
    3. Ziwei Fa & Xinchun Li & Quanlong Liu & Zunxiang Qiu & Zhengyuan Zhai, 2021. "Correlation in Causality: A Progressive Study of Hierarchical Relations within Human and Organizational Factors in Coal Mine Accidents," IJERPH, MDPI, vol. 18(9), pages 1-16, May.
    4. Garg, Muskan & Kumar, Mukesh, 2018. "The structure of word co-occurrence network for microblogs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 512(C), pages 698-720.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lin He & Dongliang Yuan & Lianwei Ren & Ming Huang & Wenyu Zhang & Jie Tan, 2023. "Evaluation Model Research of Coal Mine Intelligent Construction Based on FDEMATEL-ANP," Sustainability, MDPI, vol. 15(3), pages 1-21, January.
    2. Olga Zhironkina & Sergey Zhironkin, 2023. "Technological and Intellectual Transition to Mining 4.0: A Review," Energies, MDPI, vol. 16(3), pages 1-37, February.
    3. Jicheng Wan & Xuhui Zhang & Chao Zhang & Wenjuan Yang & Mengyu Lei & Yuyang Du & Zheng Dong, 2023. "Vision and Inertial Navigation Combined-Based Pose Measurement Method of Cantilever Roadheader," Sustainability, MDPI, vol. 15(5), pages 1-16, February.
    4. Ningning Chen & Xinqiu Fang & Minfu Liang & Xiaomei Xue & Fan Zhang & Gang Wu & Fukang Qiao, 2023. "Research on Hydraulic Support Attitude Monitoring Method Merging FBG Sensing Technology and AdaBoost Algorithm," Sustainability, MDPI, vol. 15(3), pages 1-17, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Samuel Zanferdini Oliva & Livia Oliveira-Ciabati & Denise Gazotto Dezembro & Mário Sérgio Adolfi Júnior & Maísa Carvalho Silva & Hugo Cesar Pessotti & Juliana Tarossi Pollettini, 2021. "Text structuring methods based on complex network: a systematic review," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1471-1493, February.
    2. Jiangshi Zhang & Yongtun Li & Jingru Wu & Xiaofeng Ren & Yaona Wang & Hongfu Jia & Mengyu Xie, 2024. "Constructing a Coal Mine Safety Knowledge Graph to Promote the Association and Reuse of Risk Management Empirical Knowledge," Sustainability, MDPI, vol. 16(20), pages 1-16, October.
    3. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    4. Gallego-Losada, María-Jesús & Montero-Navarro, Antonio & García-Abajo, Elisa & Gallego-Losada, Rocío, 2023. "Digital financial inclusion. Visualizing the academic literature," Research in International Business and Finance, Elsevier, vol. 64(C).
    5. Ming Tang & Huchang Liao & Zhengjun Wan & Enrique Herrera-Viedma & Marc A. Rosen, 2018. "Ten Years of Sustainability (2009 to 2018): A Bibliometric Overview," Sustainability, MDPI, vol. 10(5), pages 1-21, May.
    6. Katchanov, Yurij L. & Markova, Yulia V., 2022. "Dynamics of senses of new physics discourse: Co-keywords analysis," Journal of Informetrics, Elsevier, vol. 16(1).
    7. Yikun Su & Hong Xue & Huakang Liang, 2019. "An Evaluation Model for Urban Comprehensive Carrying Capacity: An Empirical Case from Harbin City," IJERPH, MDPI, vol. 16(3), pages 1-25, January.
    8. Wu, Hanjun & Hong Tsui, Kan Wai & Ngo, Thanh & Lin, Yi-Hsin, 2020. "Impacts of aviation subsidies on regional wellbeing: Systematic review, meta-analysis and future research directions," Transport Policy, Elsevier, vol. 99(C), pages 215-239.
    9. Xiangmei, Wang & Xiaoxiao, Geng & Wang, Yingchen, 2023. "Research on the network topology characteristics of unsafe behavior propagation in coal mine group from the perspective of human factors," Resources Policy, Elsevier, vol. 85(PA).
    10. Shakibian, Hadi & Charkari, Nasrollah Moghadam, 2018. "Statistical similarity measures for link prediction in heterogeneous complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 248-263.
    11. Gaofeng Wang & Shuai Li & Zihao Zhang & Yanning Hou & Changhoon Shin, 2023. "A Visual Knowledge Map Analysis of Cross-Border Agri-Food Supply Chain Research Based on CiteSpace," Sustainability, MDPI, vol. 15(14), pages 1-28, July.
    12. Ma, Chao-Qun & Lei, Yu-Tian & Ren, Yi-Shuai & Chen, Xun-Qi & Wang, Yi-Ran & Narayan, Seema, 2024. "Systematic analysis of the blockchain in the energy sector: Trends, issues, and future directions," Telecommunications Policy, Elsevier, vol. 48(2).
    13. Hanan Qudah & Sari Malahim & Rula Airout & Mohammad Alomari & Aiman Abu Hamour & Mohammad Alqudah, 2023. "Islamic Finance in the Era of Financial Technology: A Bibliometric Review of Future Trends," IJFS, MDPI, vol. 11(2), pages 1-29, June.
    14. Roger Jensen & David P. Gilkey, 2023. "Risk-Reduction Research in Occupational Safety and Ergonomics: An Editorial," IJERPH, MDPI, vol. 20(6), pages 1-4, March.
    15. Jiqing Liu & Gui Zhang & Xiaojing Lv & Jiayu Li, 2022. "Discovering the Landscape and Evolution of Responsible Research and Innovation (RRI): Science Mapping Based on Bibliometric Analysis," Sustainability, MDPI, vol. 14(14), pages 1-32, July.
    16. Li Yang & Xue Wang & Junqi Zhu & Liyan Sun & Zhiyuan Qin, 2022. "Comprehensive Evaluation of Deep Coal Miners’ Unsafe Behavior Based on HFACS-CM-SEM-SD," IJERPH, MDPI, vol. 19(17), pages 1-29, August.
    17. Yueran Duan & Qing Guan, 2021. "Predicting potential knowledge convergence of solar energy: bibliometric analysis based on link prediction model," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3749-3773, May.
    18. Rui-Liang Wang & Tzu-Fan Hsu & Chen-Zhong Hu, 2021. "A Bibliometric Study of Research Topics and Sustainability of Packaging in the Greater China Region," Sustainability, MDPI, vol. 13(10), pages 1-19, May.
    19. Jovani Taveira de Souza & Antonio Carlos de Francisco & Cassiano Moro Piekarski & Guilherme Francisco do Prado, 2019. "Data Mining and Machine Learning to Promote Smart Cities: A Systematic Review from 2000 to 2018," Sustainability, MDPI, vol. 11(4), pages 1-14, February.
    20. Ren, Yi-Shuai & Ma, Chao-Qun & Chen, Xun-Qi & Lei, Yu-Tian & Wang, Yi-Ran, 2023. "Sustainable finance and blockchain: A systematic review and research agenda," Research in International Business and Finance, Elsevier, vol. 64(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11650-:d:916833. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.