IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v319y2022i1d10.1007_s10479-020-03514-x.html
   My bibliography  Save this article

A deep multi-modal neural network for informative Twitter content classification during emergencies

Author

Listed:
  • Abhinav Kumar

    (National Institute of Technology Patna)

  • Jyoti Prakash Singh

    (National Institute of Technology Patna)

  • Yogesh K. Dwivedi

    (Emerging Markets Research Centre (EMaRC))

  • Nripendra P. Rana

    (University of Bradford)

Abstract

People start posting tweets containing texts, images, and videos as soon as a disaster hits an area. The analysis of these disaster-related tweet texts, images, and videos can help humanitarian response organizations in better decision-making and prioritizing their tasks. Finding the informative contents which can help in decision making out of the massive volume of Twitter content is a difficult task and require a system to filter out the informative contents. In this paper, we present a multi-modal approach to identify disaster-related informative content from the Twitter streams using text and images together. Our approach is based on long-short-term-memory and VGG-16 networks that show significant improvement in the performance, as evident from the validation result on seven different disaster-related datasets. The range of F1-score varied from 0.74 to 0.93 when tweet texts and images used together, whereas, in the case of only tweet text, it varies from 0.61 to 0.92. From this result, it is evident that the proposed multi-modal system is performing significantly well in identifying disaster-related informative social media contents.

Suggested Citation

  • Abhinav Kumar & Jyoti Prakash Singh & Yogesh K. Dwivedi & Nripendra P. Rana, 2022. "A deep multi-modal neural network for informative Twitter content classification during emergencies," Annals of Operations Research, Springer, vol. 319(1), pages 791-822, December.
    • Handle: RePEc:spr:annopr:v:319:y:2022:i:1:d:10.1007_s10479-020-03514-x
    DOI: 10.1007/s10479-020-03514-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-020-03514-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-020-03514-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jamali, Mehdi & Nejat, Ali & Ghosh, Souparno & Jin, Fang & Cao, Guofeng, 2019. "Social media data and post-disaster recovery," International Journal of Information Management, Elsevier, vol. 44(C), pages 25-37.
    2. Yogesh K. Dwivedi & Mahmud Akhter Shareef & Bhasker Mukerji & Nripendra P. Rana & Kawaljeet Kaur Kapoor, 2018. "Involvement in emergency supply chain for disaster management: a cognitive dissonance perspective," International Journal of Production Research, Taylor & Francis Journals, vol. 56(21), pages 6758-6773, November.
    3. Elbanna, Amany & Bunker, Deborah & Levine, Linda & Sleigh, Anthony, 2019. "Emergency management in the changing world of social media: Framing the research agenda with the stakeholders through engaged scholarship," International Journal of Information Management, Elsevier, vol. 47(C), pages 112-120.
    4. Kim, Jooho & Bae, Juhee & Hastak, Makarand, 2018. "Emergency information diffusion on online social media during storm Cindy in U.S," International Journal of Information Management, Elsevier, vol. 40(C), pages 153-165.
    5. Zhang, Cheng & Fan, Chao & Yao, Wenlin & Hu, Xia & Mostafavi, Ali, 2019. "Social media for intelligent public information and warning in disasters: An interdisciplinary review," International Journal of Information Management, Elsevier, vol. 49(C), pages 190-207.
    6. Rameshwar Dubey & Sadia Samar Ali & Padmanabha Aital & V.G. Venkatesh, 2014. "Mechanics of humanitarian supply chain agility and resilience and its empirical validation," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 17(4), pages 367-384.
    7. Kawaljeet Kaur Kapoor & Kuttimani Tamilmani & Nripendra P. Rana & Pushp Patil & Yogesh K. Dwivedi & Sridhar Nerur, 2018. "Advances in Social Media Research: Past, Present and Future," Information Systems Frontiers, Springer, vol. 20(3), pages 531-558, June.
    8. Jomon Paul & Govind Hariharan, 2012. "Location-allocation planning of stockpiles for effective disaster mitigation," Annals of Operations Research, Springer, vol. 196(1), pages 469-490, July.
    9. Son, Jaebong & Lee, Hyung Koo & Jin, Sung & Lee, Jintae, 2019. "Content features of tweets for effective communication during disasters: A media synchronicity theory perspective," International Journal of Information Management, Elsevier, vol. 45(C), pages 56-68.
    10. Dubey, Rameshwar & Gunasekaran, Angappa & Childe, Stephen J. & Roubaud, David & Fosso Wamba, Samuel & Giannakis, Mihalis & Foropon, Cyril, 2019. "Big data analytics and organizational culture as complements to swift trust and collaborative performance in the humanitarian supply chain," International Journal of Production Economics, Elsevier, vol. 210(C), pages 120-136.
    11. Sukho Jin & Sukjae Jeong & Jangyeop Kim & Kyungsup Kim, 2015. "A logistics model for the transport of disaster victims with various injuries and survival probabilities," Annals of Operations Research, Springer, vol. 230(1), pages 17-33, July.
    12. Akash Sinha & Prabhat Kumar & Nripendra P. Rana & Rubina Islam & Yogesh K. Dwivedi, 2019. "Impact of internet of things (IoT) in disaster management: a task-technology fit perspective," Annals of Operations Research, Springer, vol. 283(1), pages 759-794, December.
    13. 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.
    14. Jyoti Prakash Singh & Yogesh K. Dwivedi & Nripendra P. Rana & Abhinav Kumar & Kawaljeet Kaur Kapoor, 2019. "Event classification and location prediction from tweets during disasters," Annals of Operations Research, Springer, vol. 283(1), pages 737-757, December.
    15. 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.
    Full references (including those not matched with items on IDEAS)

    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. Sachin Modgil & Rohit Kumar Singh & Cyril Foropon, 2022. "Quality management in humanitarian operations and disaster relief management: a review and future research directions," Annals of Operations Research, Springer, vol. 319(1), pages 1045-1098, December.
    2. 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.
    3. Josip Marić & Carlos Galera-Zarco & Marco Opazo-Basáez, 2022. "The emergent role of digital technologies in the context of humanitarian supply chains: a systematic literature review," Annals of Operations Research, Springer, vol. 319(1), pages 1003-1044, December.
    4. Jamali, Mehdi & Nejat, Ali & Ghosh, Souparno & Jin, Fang & Cao, Guofeng, 2019. "Social media data and post-disaster recovery," International Journal of Information Management, Elsevier, vol. 44(C), pages 25-37.
    5. Jiandong Chen & Ping Wang & Jixian Zhou & Malin Song & Xinyue Zhang, 2022. "Influencing factors and efficiency of funds in humanitarian supply chains: the case of Chinese rural minimum living security funds," Annals of Operations Research, Springer, vol. 319(1), pages 413-438, December.
    6. 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.
    7. Turgut Acikara & Bo Xia & Tan Yigitcanlar & Carol Hon, 2023. "Contribution of Social Media Analytics to Disaster Response Effectiveness: A Systematic Review of the Literature," Sustainability, MDPI, vol. 15(11), pages 1-50, May.
    8. Prabhsimran Singh & Surleen Kaur & Abdullah M. Baabdullah & Yogesh K. Dwivedi & Sandeep Sharma & Ravinder Singh Sawhney & Ronnie Das, 2023. "Is #SDG13 Trending Online? Insights from Climate Change Discussions on Twitter," Information Systems Frontiers, Springer, vol. 25(1), pages 199-219, February.
    9. Nisar, Tahir M. & Prabhakar, Guru & Patil, Pushp P., 2018. "Sports clubs’ use of social media to increase spectator interest," International Journal of Information Management, Elsevier, vol. 43(C), pages 188-195.
    10. Mahmud A. Shareef & Yogesh K. Dwivedi & Vinod Kumar & D. Laurie Hughes & Ramakrishnan Raman, 2022. "Sustainable supply chain for disaster management: structural dynamics and disruptive risks," Annals of Operations Research, Springer, vol. 319(1), pages 1451-1475, December.
    11. Son, Jaebong & Lee, Hyung Koo & Jin, Sung & Lee, Jintae, 2019. "Content features of tweets for effective communication during disasters: A media synchronicity theory perspective," International Journal of Information Management, Elsevier, vol. 45(C), pages 56-68.
    12. Narayan Prasad Nagendra & Gopalakrishnan Narayanamurthy & Roger Moser, 2022. "Management of humanitarian relief operations using satellite big data analytics: the case of Kerala floods," Annals of Operations Research, Springer, vol. 319(1), pages 885-910, December.
    13. Acharya, Abhilash & Singh, Sanjay Kumar & Pereira, Vijay & Singh, Poonam, 2018. "Big data, knowledge co-creation and decision making in fashion industry," International Journal of Information Management, Elsevier, vol. 42(C), pages 90-101.
    14. Raed S. Algharabat & Nripendra P. Rana, 0. "Social Commerce in Emerging Markets and its Impact on Online Community Engagement," Information Systems Frontiers, Springer, vol. 0, pages 1-22.
    15. Aniruddh Nain & Deepika Jain & Shivam Gupta & Ashwani Kumar, 2023. "Improving First Responders' Effectiveness in Post-Disaster Scenarios Through a Hybrid Framework for Damage Assessment and Prioritization," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 24(3), pages 409-437, September.
    16. Rameshwar Dubey & David J. Bryde & Cyril Foropon & Gary Graham & Mihalis Giannakis & Deepa Bhatt Mishra, 2022. "Agility in humanitarian supply chain: an organizational information processing perspective and relational view," Annals of Operations Research, Springer, vol. 319(1), pages 559-579, December.
    17. Shuihua Han & Hu Huang & Zongwei Luo & Cyril Foropon, 2019. "Harnessing the power of crowdsourcing and Internet of Things in disaster response," Annals of Operations Research, Springer, vol. 283(1), pages 1175-1190, December.
    18. Samuel Fosso Wamba, 2022. "Humanitarian supply chain: a bibliometric analysis and future research directions," Annals of Operations Research, Springer, vol. 319(1), pages 937-963, December.
    19. Gupta, Shivam & Kar, Arpan Kumar & Baabdullah, Abdullah & Al-Khowaiter, Wassan A.A., 2018. "Big data with cognitive computing: A review for the future," International Journal of Information Management, Elsevier, vol. 42(C), pages 78-89.
    20. Jamal Al Qundus & Kosai Dabbour & Shivam Gupta & Régis Meissonier & Adrian Paschke, 2022. "Wireless sensor network for AI-based flood disaster detection," Annals of Operations Research, Springer, vol. 319(1), pages 697-719, December.

    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:spr:annopr:v:319:y:2022:i:1:d:10.1007_s10479-020-03514-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.