IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i15p8000-d603539.html
   My bibliography  Save this article

Microblog Topic-Words Detection Model for Earthquake Emergency Responses Based on Information Classification Hierarchy

Author

Listed:
  • Xiaohui Su

    (School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
    Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China)

  • Shurui Ma

    (School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
    Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China)

  • Xiaokang Qiu

    (School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China)

  • Jiabin Shi

    (School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
    Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China)

  • Xiaodong Zhang

    (College of Land Science and Technology, China Agricultural University, Beijing 100083, China)

  • Feixiang Chen

    (School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
    Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China)

Abstract

Social media data are constantly updated, numerous, and characteristically prominent. To quickly extract the needed information from the data to address earthquake emergencies, a topic-words detection model of earthquake emergency microblog messages is studied. First, a case analysis method is used to analyze microblog information after earthquake events. An earthquake emergency information classification hierarchy is constructed based on public demand. Then, subject sets of different granularities of earthquake emergency information classification are generated through the classification hierarchy. A detection model of new topic-words is studied to improve and perfect the sets of topic-words. Furthermore, the validity, timeliness, and completeness of the topic-words detection model are verified using 2201 messages obtained after the 2014 Ludian earthquake. The results show that the information acquisition time of the model is short. The validity of the whole set is 96.96%, and the average and maximum validity of single words are 78% and 100%, respectively. In the Ludian and Jiuzhaigou earthquake cases, new topic-words added to different earthquakes only reach single digits in validity. Therefore, the experiments show that the proposed model can quickly obtain effective and pertinent information after an earthquake, and the complete performance of the earthquake emergency information classification hierarchy can meet the needs of other earthquake emergencies.

Suggested Citation

  • Xiaohui Su & Shurui Ma & Xiaokang Qiu & Jiabin Shi & Xiaodong Zhang & Feixiang Chen, 2021. "Microblog Topic-Words Detection Model for Earthquake Emergency Responses Based on Information Classification Hierarchy," IJERPH, MDPI, vol. 18(15), pages 1-20, July.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:15:p:8000-:d:603539
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/15/8000/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/15/8000/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yates, Dave & Paquette, Scott, 2011. "Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake," International Journal of Information Management, Elsevier, vol. 31(1), pages 6-13.
    2. Xuesong Bai & Xiaoxue Liu & Shuhan Lu & Xiaodong Zhang & Wei Su & Xiaohui Su & Lin Li, 2020. "SEPM: rapid seism emergency information processing based on social media," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(1), pages 659-679, October.
    3. Thomas J. Huggins & Raj Prasanna, 2020. "Information Technologies Supporting Emergency Management Controllers in New Zealand," Sustainability, MDPI, vol. 12(9), pages 1-16, May.
    4. Xu Liu & Bihan Tang & Hongyang Yang & Yuan Liu & Chen Xue & Lulu Zhang, 2015. "The Technical Efficiency of Earthquake Medical Rapid Response Teams Following Disasters: The Case of the 2010 Yushu Earthquake in China," IJERPH, MDPI, vol. 12(12), pages 1-10, December.
    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. Shasha Li & Xinyu Peng & Ruiqiu Pang & Li Li & Zixuan Song & Hongying Ye, 2021. "Information Preference and Information Supply Efficiency Evaluation before, during, and after an Earthquake: Evidence from Songyuan, China," IJERPH, MDPI, vol. 18(24), pages 1-28, December.

    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. Feng Wu & Wanqiang Xu & Chaoran Lin & Yanwei Zhang, 2022. "Knowledge Trajectories on Public Crisis Management Research from Massive Literature Text Using Topic-Clustered Evolution Extraction," Mathematics, MDPI, vol. 10(12), pages 1-18, June.
    2. Muhammad Ashraf Fauzi, 2023. "Social media in disaster management: review of the literature and future trends through bibliometric analysis," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 118(2), pages 953-975, September.
    3. Ni, Zi-jian & Rong, Lili & Wang, Ning & Cao, Shuo, 2019. "Knowledge model for emergency response based on contingency planning system of China," International Journal of Information Management, Elsevier, vol. 46(C), pages 10-22.
    4. Zhao, Dingtao & Wang, Feng & Wei, Jiuchang & Liang, Liang, 2013. "Public reaction to information release for crisis discourse by organization: Integration of online comments," International Journal of Information Management, Elsevier, vol. 33(3), pages 485-495.
    5. S M Nadim Sultan & Keshav Lall Maharjan, 2022. "Cyclone-Induced Disaster Loss Reduction by Social Media: A Case Study on Cyclone Amphan in Koyra Upazila, Khulna District, Bangladesh," Sustainability, MDPI, vol. 14(21), pages 1-17, October.
    6. Kim, Jooho & Hastak, Makarand, 2018. "Social network analysis: Characteristics of online social networks after a disaster," International Journal of Information Management, Elsevier, vol. 38(1), pages 86-96.
    7. Siqing Shan & Tenglong Xin & Li Wang & You Li & Ling Li, 2013. "Identifying Influential Factors of Knowledge Sharing in Emergency Events: A Virtual Community Perspective," Systems Research and Behavioral Science, Wiley Blackwell, vol. 30(3), pages 367-382, May.
    8. Pogrebnyakov, Nicolai & Maldonado, Edgar, 2018. "Didn’t roger that: Social media message complexity and situational awareness of emergency responders," International Journal of Information Management, Elsevier, vol. 40(C), pages 166-174.
    9. Ghezzi, Antonio & Gastaldi, Luca & Lettieri, Emanuele & Martini, Antonella & Corso, Mariano, 2016. "A role for startups in unleashing the disruptive power of social media," International Journal of Information Management, Elsevier, vol. 36(6), pages 1152-1159.
    10. Sarah Gardiner & Jinyan Chen & Margarida Abreu Novais & Karine Dupré & J. Guy Castley, 2023. "Analyzing and Leveraging Social Media Disaster Communication of Natural Hazards: Community Sentiment and Messaging Regarding the Australian 2019/20 Bushfires," Societies, MDPI, vol. 13(6), pages 1-20, May.
    11. Deepthi Kolady & Amrit Dumre & Weiwei Zhang & Kaiqun Fu & Marcia O'Leary & Laura Rose, 2023. "Social media use among American Indians in South Dakota: Preferences and perceptions," Papers 2307.01404, arXiv.org.
    12. Wenwen Zhang & Camille Barchers & Janille Smith-Colin, 2023. "Transit communication via Twitter during the COVID-19 pandemic," Environment and Planning B, , vol. 50(5), pages 1244-1261, June.
    13. Pacauskas, Darius & Rajala, Risto & Westerlund, Mika & Mäntymäki, Matti, 2018. "Harnessing user innovation for social media marketing: Case study of a crowdsourced hamburger," International Journal of Information Management, Elsevier, vol. 43(C), pages 319-327.
    14. John B. Coles & Jing Zhang & Jun Zhuang, 2022. "Bridging the research-practice gap in disaster relief: using the IFRC Code of Conduct to develop an aid model," Annals of Operations Research, Springer, vol. 312(2), pages 1337-1357, May.
    15. Mele, Emanuele & Filieri, Raffaele & De Carlo, Manuela, 2023. "Pictures of a crisis. Destination marketing organizations’ Instagram communication before and during a global health crisis," Journal of Business Research, Elsevier, vol. 163(C).
    16. Shasha Li & Xinyu Peng & Ruiqiu Pang & Li Li & Zixuan Song & Hongying Ye, 2021. "Information Preference and Information Supply Efficiency Evaluation before, during, and after an Earthquake: Evidence from Songyuan, China," IJERPH, MDPI, vol. 18(24), pages 1-28, December.
    17. Mahnoosh Hassankhani & Mehdi Alidadi & Ayyoob Sharifi & Abolghasem Azhdari, 2021. "Smart City and Crisis Management: Lessons for the COVID-19 Pandemic," IJERPH, MDPI, vol. 18(15), pages 1-18, July.
    18. Simon, Tomer & Goldberg, Avishay & Adini, Bruria, 2015. "Socializing in emergencies—A review of the use of social media in emergency situations," International Journal of Information Management, Elsevier, vol. 35(5), pages 609-619.
    19. Ragini, J. Rexiline & Anand, P.M. Rubesh & Bhaskar, Vidhyacharan, 2018. "Big data analytics for disaster response and recovery through sentiment analysis," International Journal of Information Management, Elsevier, vol. 42(C), pages 13-24.
    20. Martínez-Rojas, María & Pardo-Ferreira, María del Carmen & Rubio-Romero, Juan Carlos, 2018. "Twitter as a tool for the management and analysis of emergency situations: A systematic literature review," International Journal of Information Management, Elsevier, vol. 43(C), pages 196-208.

    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:jijerp:v:18:y:2021:i:15:p:8000-:d:603539. 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.