Systematic Analysis of Crowdsourcing Support for Collaborative Crisis Communication: A Literature Review and User Experience Evaluation

Maria Clara Pestana; Ailton Ribeiro; Vaninha Vieira

doi:10.5753/jis.2026.5433

Authors

Maria Clara Pestana Federal University of Bahia https://orcid.org/0000-0001-8382-7844
Ailton Ribeiro Federal University of Bahia https://orcid.org/0000-0003-4524-2188
Vaninha Vieira Federal University of Bahia https://orcid.org/0000-0002-3424-8413

DOI:

https://doi.org/10.5753/jis.2026.5433

Keywords:

Crowdsourcing, Collaboration, Crisis Communication

Abstract

Background: This article examines the application of crowdsourcing solutions in collaborative crisis communication, focusing on the challenges faced by crisis and emergency responders, as well as the collaborative potential offered by digital platforms. Purpose: The primary objective of this study is to explore and categorize the challenges encountered in collaboration among stakeholders during crises and emergencies. The secondary research goal aims to assess how crowdsourcing solutions, such as crowdfunding, contribute to enhancing communication and coordination in crisis management. Methods: To achieve these objectives, a systematic literature review was conducted, categorizing the key challenges faced in crisis scenarios and the system requirements that crowdsourcing solutions must address. Furthermore, an evaluation of User Experience (UX) in crowdfunding campaigns during humanitarian crises was performed, investigating factors that influence donations, donor concerns, and the challenges involved in mobilizing volunteers and resources. Results: The analysis identified key entities in crisis communication: the crowd, agents (authorities and professionals), and the environment (platforms, apps, or maps). Requirements emphasized trust, rapid response, efficient coordination, active engagement, and transparency. Challenges included issues with transparency, authenticity, and security. The reputation of institutions was crucial for donations, and participants valued access to updated information and communication channels with institutions. Conclusion: Crowd collaboration enhances data sharing, transparency, and resource allocation in crisis scenarios through crowdsourcing solutions. Challenges in developing these solutions include ensuring trust, validating data, and coordinating rapid responses. Similarly, crowdfunding platforms face challenges related to concerns about authenticity and transparency, which significantly influence donation decisions.

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References

Animas, S. D. and Gunay, N. S. (2022). PEERS: A Community-based Geo-social Information Collaboration Framework for Public Safety and Security. In 2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), pages 1–6. IEEE. DOI: https://doi.org/10.1109/HNICEM57413.2022.10109493.

Bannerman, S. (2013). Crowdfunding culture. Wi: Journal of Mobile Culture, 7(1).

Behl, A., Dutta, P., Sheorey, P., and Singh, R. K. (2023). Examining the role of dialogic communication and trust in donation-based crowdfunding tasks using information quality perspective. TQM Journal, 35(1). DOI: https://doi.org/10.1108/TQM-06-2020-0139.

Benali, M. and Ghomari, A. R. (2017). Towards a crowdsourcing-based approach to enhance decision making in collaborative crisis management. volume 2017-May.

Brabham, D. (2013). Using Crowdsourcing In Government. IBM Cent. Bus. Gov., pages 1–42.

Brown, A., Franken, P., Bonner, S., Dolezal, N., and Moross, J. (2016). Safecast: successful citizen-science for radiation measurement and communication after fukushima. Journal of Radiological Protection, 36(2):S82. DOI: https://doi.org/10.1088/0952-4746/36/2/S82.

Calderon, A., Hinds, J., and Johnson, P. (2014). Intcris: A tool for enhanced communication and collective decision-making during crises. In Information Systems for Crisis Response and Management.

Câmara, J. H., Vegi, L. F., Pereira, R. O., Geöcze, Z. A., Lisboa-Filho, J., and de Souza, W. D. (2017). Clickonmap: a platform for development of volunteered geographic information systems. In 2017 12th Iberian Conference on Information Systems and Technologies (CISTI), pages 1–6. IEEE. DOI: https://doi.org/10.23919/CISTI.2017.7975776.

Camarinha-Matos, L. M. and Afsarmanesh, H. (2005). Collaborative networks: A new scientific discipline. Journal of Intelligent Manufacturing, 16(4-5). DOI: https://doi.org/10.1007/s10845-005-1656-3.

Dixon, B. and Johns, R. (2019). Vision for a holistic smart city-hsc: Integrating resiliency framework via crowdsourced community resiliency information system (cris). In Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances on Resilient and Intelligent Cities, ARIC'19, pages 1–4, New York, NY, USA. Association for Computing Machinery. DOI: https://doi.org/10.1145/3356395.3365541.

El Abdallaoui, H. E. A., Mohamed, S., et al. (2016). Finding a lost child using a crowdsourcing framework. In 2016 4th International Conference on Control Engineering and Information Technology (CEIT), pages 1–6. IEEE. DOI: https://doi.org/10.1109/CEIT.2016.7929047.

El Alaoui El Abdallaoui, H., El Fazziki, A., Sadiq, A., Ennaji, F. Z., and Sadgal, M. (2016). How can crowdsourcing help in crisis situations? Missing kids case study. In 2016 IEEE/ACS 13th International Conference of Computer Systems and Applications (AICCSA), pages 1–7. IEEE. DOI: https://doi.org/10.1109/AICCSA.2016.7945793.

Ernst, C., Mladenow, A., and Strauss, C. (2017). Collaboration and crowdsourcing in emergency management. International Journal of Pervasive Computing and Communications, 13(2):176–193. DOI: https://doi.org/10.1108/IJPCC-03-2017-0026.

Estellés-Arolas, E., Navarro-Giner, R., and González-Ladrón-De-Guevara, F. (2015). Crowdsourcing fundamentals: Definition and typology. In Advances in Crowdsourcing, pages 33–48. Springer International Publishing. DOI: https://doi.org/10.1007/978-3-319-18341-1_3.

European Commission and Directorate-General for Internal Market, Industry, Entrepreneurship and SMEs (2015). Crowdfunding explained – A guide for small and medium enterprises on crowdfunding and how to use it. Publications Office.

Farber, J., Myers, T., Trevathan, J., Atkinson, I., and Andersen, T. (2012). Riskr: A low-technological web2. 0 disaster service to monitor and share information. In 2012 15th International Conference on Network-Based Information Systems, pages 311–318. IEEE. DOI: https://doi.org/10.1109/NBiS.2012.12.

Fulco, F., Inoguchi, M., and Mikami, T. (2018). Cyber-physical disaster drill: Preliminary results and social challenges of the first attempts to unify human, ict and ai in disaster response. In 2018 IEEE International Conference on Big Data (Big Data), pages 3495–3497. IEEE. DOI: https://doi.org/10.1109/BigData.2018.8622266.

Gadiraju, U., Kawase, R., and Dietze, S. (2014). A taxonomy of microtasks on the web. In Proceedings of the 25th ACM conference on Hypertext and social media, pages 218–223. DOI: https://doi.org/10.1145/2631775.2631819.

Garcia, L., Parra, L., Taha, M., and Lloret, J. (2018). System for Detection of Emergency Situations in Smart City Environments Employing Smartphones. In 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pages 266–272. IEEE. DOI: https://doi.org/10.1109/ICACCI.2018.8554654.

Google Trends (2024). Google trends explore (brazil, 2024): "enchentes rs" vs. "vaquinha" vs. "ushahidi". [link]. Accessed on 01 August 2026.

Hasse, D. and De Rolt, C. R. (2017). Collega semantic middleware for collaborative assistance in mobile social networks. In 2017 AEIT International Annual Conference, pages 1–6. IEEE. DOI: http://doi.org/10.23919/AEIT.2017.8240553.

Hassenzahl, M. (2004). The Thing and I: Understanding the Relationship Between User and Product, pages 31–42. Springer Netherlands, Dordrecht. DOI: https://doi.org/10.1007/1-4020-2967-5_4.

Howe, J. et al. (2006). The rise of crowdsourcing. Wired magazine, 14(6):1–4.

Kitchenham, B. (2004). Procedures for performing systematic reviews. Keele, UK, Keele University, 33(2004):1–26.

Kuehn, A., Kaschewsky, M., Kappeler, A., Spichiger, A., and Riedl, R. (2011). Interoperability and information brokers in public safety: An approach toward seamless emergency communications. Journal of theoretical and applied electronic commerce research, 6:43 – 60. DOI: https://doi.org/10.4067/S0718-18762011000100005.

Ludwig, T., Kotthaus, C., Reuter, C., Van Dongen, S., and Pipek, V. (2016). Situated crowdsourcing during disasters: Managing the tasks of spontaneous volunteers through public displays. International Journal of Human-Computer Studies, 102:103–121. DOI: https://doi.org/10.1016/j.ijhcs.2016.09.008.

MacRi, D., Gentile, A. F., and Sabatino, P. (2023). An IoT-based Approach to Expert Recommendation in Community Question Answering for Disaster Recovery. In IEEE International Conference on Data Mining Workshops, ICDMW, pages 860–867. IEEE. DOI: https://doi.org/10.1109/ICDMW60847.2023.00116.

McKnight, D. H., Choudhury, V., and Kacmar, C. (2002). Developing and validating trust measures for e-commerce: An integrative typology. Information Systems Research, 13(3):334–359. DOI: https://doi.org/10.1287/isre.13.3.334.81.

Mizushima, K., Sugihara, T., and Ikawa, Y. (2012). Knowledge management in a volunteer community at the time of disaster. In *2012 Proceedings of Portland International Center for Management of Engineering and Technology: Technology Management for Emerging Technologies, PICMET'12*, pages 2274–2282.

Mollick, E. (2014). The dynamics of crowdfunding: An exploratory study. Journal of Business Venturing, 29(1):1–16. DOI: https://doi.org/10.1016/j.jbusvent.2013.06.005.

Monares, A., Ochoa, S. F., Herskovic, V., Santos, R., and Pino, J. A. (2014). Modeling interactions in human-centric wireless sensor networks. In Proceedings of the 2014 IEEE 18th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pages 661–666. IEEE. DOI: https://doi.org/10.1109/CSCWD.2014.6846923.

Mota, J. M. B. and Lima, A. C. (2018). Efetividade do crowdsourcing como apoio à segurança pública. Revista de Administração Contemporânea, 22(5). DOI: https://doi.org/10.1590/1982-7849rac2018180007.

Norris, W., Voida, A., and Voida, S. (2022). People talk in stories. responders talk in data: A framework for temporal sensemaking in time-and safety-critical work. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW1):1–23. DOI: https://doi.org/10.1145/3512955.

Pestana, M., Ribeiro, A., and Vieira, V. (2024). Crowdsourcing for collaborative crisis communication: a systematic review. In Anais do XIX Simpósio Brasileiro de Sistemas Colaborativos, pages 71–84, Porto Alegre, RS, Brasil. SBC. DOI: https://doi.org/10.5753/sbsc.2024.237802.

Pestana, M. and Vieira, V. (2024). United for humanity: Developing a collaborative model for crowd engagement in crisis recovery campaigns. In Anais do XIX Simpósio Brasileiro de Sistemas Colaborativos, pages 210–218, Porto Alegre, RS, Brasil. SBC. DOI: https://doi.org/10.5753/sbsc.2024.237886.

Pezzica, C., Cutini, V., and Bleil de Souza, C. (2019). Rapid configurational analysis using osm data: Towards the use of space syntax to orient post-disaster decision making. In Proceedings of the 12th International Space Syntax Symposium (12SSS), volume 3, Beijing, China. Space Syntax Network/Sejong University Press.

Pfleeger, S. L. and Kitchenham, B. A. (2001). Principles of survey research: Part 1: Turning lemons into lemonade. SIGSOFT Softw. Eng. Notes, 26(6):16–18. DOI: https://doi.org/10.1145/505532.505535.

Pradhan, M. (2021). Federation Based on MQTT for Urban Humanitarian Assistance and Disaster Recovery Operations. IEEE Communications Magazine, 59(2):43–49. DOI: https://doi.org/10.1109/MCOM.001.2000937.

Preece, A., Webberley, W., Braines, D., Zaroukian, E. G., and Bakdash, J. Z. (2017). Sherlock: Experimental Evaluation of a Conversational Agent for Mobile Information Tasks. IEEE Transactions on Human-Machine Systems, 47(6):1017–1028. DOI: https://doi.org/10.1109/THMS.2017.2700625.

Quarantelli, E. L. and Dynes, R. R. (1977). Response to social crisis and disaster. Annual Review of Sociology, 3:23–49. DOI: https://doi.org/10.1146/annurev.so.03.080177.000323.

Quintanilha, C. B., Borges, M. R. S., and Vivacqua, A. S. (2011). Social networks and emergency: From society to the command room. In Proceedings of the 2011 15th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pages 538–543. IEEE. DOI: https://doi.org/10.1109/CSCWD.2011.5960124.

Samir, E., Azab, M., and Jung, Y. (2019). Blockchain guided trustworthy interactions for distributed disaster management. In 2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON), pages 0241–0245. IEEE. DOI: https://doi.org/10.1109/IEMCON.2019.8936147.

Shih, C.-S., Chen, L.-J., Lin, C.-J., and Chung, W.-H. (2012). Open information gateway for disaster management. In 2012 IEEE International Conference on Communications (ICC), pages 6348–6352. IEEE. DOI: https://doi.org/10.1109/ICC.2012.6364969.

Tserstou, A., Jonoski, A., Popescu, I., Asumpcao, T. H., Athanasiou, G., Kallioras, A., and Nichersu, I. (2017). SCENT: Citizen Sourced Data in Support of Environmental Monitoring. In 2017 21st International Conference on Control Systems and Computer Science (CSCS), pages 612–616. IEEE. DOI: https://doi.org/10.1109/CSCS.2017.93.

Turner, P. (2017). A Psychology of User Experience: Involvement, Affect and Aesthetics. Human-Computer Interaction Series. Springer International Publishing, 1 edition.

van den Homberg, M. and Neef, M. (2015). Towards novel community-based collaborative disaster management approaches in the new information environment: an ngo perspective. Planet@ Risk, 3(1).

Zelenkauskaite, A., Bessis, N., Sotiriadis, S., and Asimakopoulou, E. (2012). Disaster management and profile modelling of IoT objects: Conceptual parameters for interlinked objects in relation to social network analysis. In Proceedings of the 2012 4th International Conference on Intelligent Networking and Collaborative Systems, INCoS 2012, pages 509–514. DOI: https://doi.org/10.1109/iNCoS.2012.26.

Zhang, Y., Zong, R., Kou, Z., Shang, L., and Wang, D. (2022). On streaming disaster damage assessment in social sensing: A crowd-driven dynamic neural architecture searching approach. Knowledge-Based Systems, 239:107984. DOI: https://doi.org/10.1016/j.knosys.2021.107984.