2692-4048ISSN (Online)
2770-0070ISSN (Print)
Volume 14 , Issue 2 , PP: 227-243, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Ali S. Abed Al Sailawi 1 * , Mohammad Reza Kangavari 2
Doi: https://doi.org/10.54216/FPA.140219
In the past three years, social media has had a significant impact on our lives, including crisis management. The COVID-19 pandemic highlighted the importance of accurate information and exposed the spread of false information. This paper specifically examines the COVID-19 crisis and analyzes relevant literature to provide insights for national authorities and organizations. Utilizing social media data for crisis management poses challenges due to its unstructured nature. To overcome this, the paper proposes a comprehensive method that addresses all aspects of long-term crisis management. This method relies on labeled and structured information for accurate sentiment analysis and classification. An automated approach is presented to annotate and classify tweet texts, reducing manual labeling and improving classifier accuracy. The framework involves generating topics using Latent Dirichlet Allocation (LDA) and ranking them with a new algorithm for data annotation. The labeled text is transformed into feature representation using Bert embeddings, which can be utilized in deep learning models for categorizing textual data. The primary aim of this paper is to offer valuable insights and resources to researchers studying crisis management through social media literature, with a specific focus on high-accuracy sentiment analysis.
COVID-19 pandemic , Social Medias , Long-Lasting Crisis Management.
[1] Mayopu, R.G., L.-S. Chen, and V. Nalluri, Classification Crisis Communication: Semiotic Approach with Latent Semantic Analysis. Engineering Proceedings, 2023. 38(1): p. 9.
[2] Hassankhani, M., et al., Smart city and crisis management: Lessons for the COVID-19 pandemic. International Journal of Environmental Research and Public Health, 2021. 18(15): p. 7736.
[3] Rodrigues, M., et al., Reviewing COVID-19 Literature on Business Management: What It Portends for Future Research? Sustainability, 2021. 13(11): p. 5995.
[4] Petak, W.J., Emergency management: A challenge for public administration. Public Administration Review, 1985. 45: p. 3-7.
[5] Lettieri, E., C. Masella, and G. Radaelli, Disaster management: findings from a systematic review. Disaster Prevention and Management: An International Journal, 2009. 18(2): p. 117-136.
[6] Moe, T.L. and P. Pathranarakul, An integrated approach to natural disaster management: public project management and its critical success factors. Disaster Prevention and Management: An International Journal, 2006. 15(3): p. 396-413.
[7] Dotzlaw, K., et al. Mining Big Healthcare Data to Predict Long COVID Cases. in 2023 IEEE International Conference on Industrial Technology (ICIT). 2023. IEEE.
[8] Zhang, S., et al., Data-Driven System-Level Design Framework for Responsible Cyber-Physical-Social Systems. Computer, 2023. 56(4): p. 80-91.
[9] Raue, S., C. Johnson, and T. Storer, (SMA) 2-a Social Media Audience Sharing Model for Authorities to support effective crisis communication. 2012.
[10] Zhao, D. and M.B. Rosson. How and why people Twitter: the role that micro-blogging plays in informal communication at work. in Proceedings of the 2009 ACM International Conference on Supporting Group Work. 2009.
[11] Nalluru, G., R. Pandey, and H. Purohit. Relevancy classification of multimodal social media streams for emergency services. in 2019 IEEE International Conference on Smart Computing (SMARTCOMP). 2019. IEEE.
[12] Fischer, D., O. Posegga, and K. Fischbach. Communication Barriers in Crisis Management: a literature Review. in ECIS. 2016.
[13] Shahbazi, M., et al., Tweeting from the shadows: Social media convergence behaviour during the 2017 Iran-Iraq earthquake. Proceedings of ISCRAM Asia Pacific, 2018.
[14] Ahmed, A., Use of social media in disaster management. 2011.
[15] Fraustino, J.D., B. Liu, and Y. Jin, Social media use during disasters: a review of the knowledge base and gaps. 2012.
[16] Stieglitz, S., et al., Sensemaking and communication roles in social media crisis communication. 2017.
[17] Mirbabaie, M. and S. Youn, Exploring sense-making activities in crisis situations. Proceedings of the 10th Multikonferenz Wirtschaftsinformatik (MKWI), 2018: p. 1656-1667.
[18] Procopio, C.H. and S.T. Procopio, Do you know what it means to miss New Orleans? Internet communication, geographic community, and social capital in crisis. Journal of applied communication research, 2007. 35(1): p. 67-87.
[19] Imran, M., et al., Processing social media messages in mass emergency: A survey. ACM Computing Surveys (CSUR), 2015. 47(4): p. 1-38.
[20] Bunker, D., et al. Crisis management and social media: Assuring effective information governance for long term social sustainability. in 2013 IEEE International Conference on Technologies for Homeland Security (HST). 2013. IEEE.
[21] Reuter, C., O. Heger, and V. Pipek. Combining real and virtual volunteers through social media. in Iscram. 2013.
[22] Leung, C.K., G. Pasi, and L. Wang, Theoretical and practical data science and analytics: challenges and solutions. International Journal of Data Science and Analytics, 2023. 16(4): p. 403-406.
[23] Bruns, A. and J. Burgess, # qldfloods and@ QPSMedia: Crisis communication on Twitter in the 2011 south east Queensland floods. 2012.
[24] Plotnick, L. and S.R. Hiltz, Barriers to use of social media by emergency managers. Journal of Homeland Security and Emergency Management, 2016. 13(2): p. 247-277.
[25] Brajawidagda, U., Public value creation through social media networks: Mixed methods research on Indonesia's disaster management agencies. 2016.
[26] Endsley, M.R., B. Bolté, and D.G. Jones, Designing for situation awareness: An approach to user-centered design. 2003: CRC press.
[27] Steinberger, F., Risky gadgets to the rescue: Reframing in-car technology use as task engagement. 2018, Queensland University of Technology.
[28] Abboodi, B., S.F. Pileggi, and G. Bharathy, Social Networks in Crisis Management: A Literature Review to Address the Criticality of the Challenge. Encyclopedia, 2023. 3(3): p. 1157-1177.
[29] Akhgar, B., A. Staniforth, and D. Waddington, Application of social media in crisis management. 2017: Springer.
[30] Abbas, J., et al., The role of social media in the advent of COVID-19 pandemic: crisis management, mental health challenges and implications. Risk management and healthcare policy, 2021: p. 1917-1932.
[31] Sixsmith, A., COVID-19 and AgeTech. Quality in Ageing and Older Adults, 2020. 21(4): p. 247-252.
[32] Singh, T., et al., Post-COVID green supply chain management of used products: a study towards awareness for vaccination. Environmental Science and Pollution Research, 2023. 30(15): p. 42526-42540.
[33] Taghipour, A., et al., A robust vaccine supply chain model in pandemics: Case of Covid-19 in Iran. Computers & Industrial Engineering, 2023. 183: p. 109465.
[34] Chan, J.C., The role of social media in crisis preparedness, response and recovery. Public Relations Research, 2014. 8(4): p. 279-295.
[35] Jurgens, M. and I. Helsloot, The effect of social media on the dynamics of (self) resilience during disasters: A literature review. Journal of Contingencies and Crisis Management, 2018. 26(1): p. 79-88.
[36] Zafarani-Moattar, E., M.R. Kangavari, and A.M. Rahmani, Topic Detection on COVID-19 Tweets: A Comparative Study on Clustering and Transfer Learning Models. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 2022. 52(4): p. 281-291.
[37] MacEachren, A.M., et al. Senseplace2: Geotwitter analytics support for situational awareness. in 2011 IEEE conference on visual analytics science and technology (VAST). 2011. IEEE.
[38] Humayoun, S.R. and S. Chimote. An Interactive Visualization Tool to Explore People’s Tweets towards COVID-19. in Proceedings of the 2022 International Conference on Advanced Visual Interfaces. 2022.
[39] Saroj, A. and S. Pal, Use of social media in crisis management: A survey. International Journal of Disaster Risk Reduction, 2020. 48: p. 101584.
[40] Akhgar, B., et al. Social media in crisis events: Open networks and collaboration supporting disaster response and recovery. in 2013 IEEE International conference on technologies for Homeland Security (HST). 2013. IEEE.
[41] Asadzadeh, A., et al., Information technology in emergency management of COVID-19 outbreak. Informatics in medicine unlocked, 2020. 21: p. 100475.
[42] Stieglitz, S., et al., The Adoption of social media analytics for crisis management–Challenges and Opportunities. 2018.
[43] Abboodi, B., S.F. Pileggi, and G. Bharathy, Social Networks in Crisis Management: a Concise Literature Review. 2023.
[44] Shen, C., Y. Wang, and A.T.-K. Ho, Unpacking the black box: An investigation of online crisis communication patterns among stakeholders in the NIMBY conflict. Cities, 2023. 132: p. 104098.
[45] Lindner, R., J. Hernantes, and C. Jaca, Increasing stakeholder engagement in research projects through standardization activities. International Journal of Managing Projects in Business, 2023.
[46] Oktavianus, J. and W.-Y. Lin, Soliciting social support from migrant domestic workers’ connections to storytelling networks during a public health crisis. Health Communication, 2023. 38(6): p. 1179-1188.
[47] Zenone, M., N. Kenworthy, and N. Maani, The social media industry as a commercial determinant of health. International Journal of Health Policy and Management, 2023. 12.
[48] Firouzi, F., et al., A decision tree-based approach for determining low bone mineral density in inflammatory bowel disease using WEKA software. European journal of gastroenterology & hepatology, 2007. 19(12): p. 1075-1081.
[49] Soleymani, M.R., et al., COVID‐19 information seeking needs and behaviour among citizens in Isfahan, Iran: a qualitative study. Health Information & Libraries Journal, 2023. 40(4): p. 359-370.
[50] Shamji, M.H., et al., EAACI guidelines on environmental science in allergic diseases and asthma–Leveraging artificial intelligence and machine learning to develop a causality model in exposomics. Allergy, 2023.
[51] Saxena, D., et al. Rethinking" Risk" in Algorithmic Systems Through A Computational Narrative Analysis of Casenotes in Child-Welfare. in Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems. 2023.
[52] Deejay, A., et al., Navigating a public health crisis: Governance and sensemaking during the COVID-19 pandemic in Australia. SSM-Qualitative Research in Health, 2023. 4: p. 100317.
[53] Jungwirth, D. and D. Haluza, Artificial intelligence and public health: an exploratory study. International Journal of Environmental Research and Public Health, 2023. 20(5): p. 4541.
[54] Signorini, A., A.M. Segre, and P.M. Polgreen, The use of Twitter to track levels of disease activity and public concern in the US during the influenza A H1N1 pandemic. PloS one, 2011. 6(5): p. e19467.
[55] Ma, N., et al., Quantified multidimensional public sentiment characteristics on social media for public opinion management: Evidence from the COVID-19 pandemic. Frontiers in Public Health, 2023. 11: p. 1097796.
[56] Sun, X., et al., Social media use for coping with stress and psychological adjustment: A transactional model of stress and coping perspective. Frontiers in Psychology, 2023. 14: p. 1140312.
[57] Steinberger, P. and H. Kim, Social comparison of ability and fear of missing out mediate the relationship between subjective well-being and social network site addiction. Frontiers in Psychology, 2023. 14.
[58] Mensah, I.K., et al., The moderating influence of perceived government information transparency on COVID-19 pandemic information adoption on social media systems. Frontiers in Psychology, 2023. 14: p. 1172094.
[59] Alon-Tirosh, M. and N. Meir, Use of social network sites among adolescents with autism spectrum disorder: a qualitative study. Frontiers in Psychology, 2023. 14.
[60] Zhao, Y., et al., Chinese public's attention to the COVID-19 epidemic on social media: observational descriptive study. Journal of medical Internet research, 2020. 22(5): p. e18825.
[61] Han, X. and J. Wang, Using social media to mine and analyze public sentiment during a disaster: A case study of the 2018 Shouguang city flood in China. ISPRS International Journal of Geo-Information, 2019. 8(4): p. 185.
[62] Allington, D., et al., Health-protective behaviour, social media usage and conspiracy belief during the COVID-19 public health emergency. Psychological medicine, 2021. 51(10): p. 1763-1769.
[63] Hill, T., R. Canniford, and G.M. Eckhardt, The roar of the crowd: how interaction ritual chains create social atmospheres. Journal of Marketing, 2022. 86(3): p. 121-139.
[64] Beaudoin, C.E. and T. Hong, Emotions in the time of coronavirus: Antecedents of digital and social media use among Millennials. Computers in Human Behavior, 2021. 123: p. 106876.
[65] Malecki, K.M., J.A. Keating, and N. Safdar, Crisis communication and public perception of COVID-19 risk in the era of social media. Clinical infectious diseases, 2021. 72(4): p. 697-702.
[66] Kwok, S.W.H., S.K. Vadde, and G. Wang, Tweet topics and sentiments relating to COVID-19 vaccination among Australian Twitter users: machine learning analysis. Journal of medical Internet research, 2021. 23(5): p. e26953.
[67] Paul, I., S. Mohanty, and R. Sengupta, The role of social virtual world in increasing psychological resilience during the on-going COVID-19 pandemic. Computers in human behavior, 2022. 127: p. 107036.
[68] Brailovskaia, J. and J. Margraf, The relationship between burden caused by coronavirus (Covid-19), addictive social media use, sense of control and anxiety. Computers in Human Behavior, 2021. 119: p. 106720.
[69] Aoun, G. and K. Aoun Barakat, The use of social media for crisis communication during the COVID-19 pandemic: The case of Lebanon. Projectics/Proyéctica/Projectique, 2023. 34(1): p. 11-24.
[70] Chon, M.-G. and S. Kim, Dealing with the COVID-19 crisis: Theoretical application of social media analytics in government crisis management. Public relations review, 2022. 48(3): p. 102201.
[71] Zhou, Y., et al., Social media efficacy in crisis management: effectiveness of non-pharmaceutical interventions to manage COVID-19 challenges. Frontiers in psychiatry, 2022. 12: p. 626134.
[72] Li, Y., Y. Chandra, and N. Kapucu, Crisis coordination and the role of social media in response to COVID-19 in Wuhan, China. The American Review of Public Administration, 2020. 50(6-7): p. 698-705.
[73] Bukar, U.A., et al., How social media crisis response and social interaction is helping people recover from Covid-19: an empirical investigation. Journal of computational social science, 2022: p. 1-29.
[74] Van Dijck, J. and D. Alinejad, Social media and trust in scientific expertise: Debating the Covid-19 pandemic in the Netherlands. Social Media+ Society, 2020. 6(4): p. 2056305120981057.
[75] Yu, M., et al., Communication related health crisis on social media: a case of COVID-19 outbreak. Current issues in tourism, 2021. 24(19): p. 2699-2705.
[76] Park, Y.-E., Developing a COVID-19 crisis management strategy using news media and social media in big data analytics. Social Science Computer Review, 2022. 40(6): p. 1358-1375.
[77] Cheng, P., et al., COVID-19 epidemic peer support and crisis intervention via social media. Community mental health journal, 2020. 56: p. 786-792.
[78] Chen, Y., et al. Automatically labeled data generation for large scale event extraction. in Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2017.
[79] Karami, A., et al., Twitter speaks: A case of national disaster situational awareness. Journal of Information Science, 2020. 46(3): p. 313-324.
[80] Xin, Z., et al. Automatic annotation of text classification data set in specific field using named entity recognition. in 2019 IEEE 19th International Conference on Communication Technology (ICCT). 2019. IEEE.
[81] Alrashdi, R. and S. O'Keefe. Automatic labeling of tweets for crisis response using distant supervision. in Companion Proceedings of the Web Conference 2020. 2020.
[82] Win, S.S.M. and T.N. Aung, Automated text annotation for social media data during natural disasters. 2018, MERAL Portal.
[83] Gupta, I. and N. Joshi, Real-time twitter corpus labelling using automatic clustering approach. International Journal of Computing and Digital Systems, 2021. 10: p. 519-532.