Improving coordination and communication in disaster relief operations via Social Media Analysis- Group 2

2023-2024 Spring
Faculty Department of Project Supervisor: 
Faculty of Engineering and Natural Sciences
Number of Students: 

Project Description and Objective
In times of catastrophe, such as natural disasters or humanitarian crises, effective communication and coordination of aid resources can be a critical challenge. The confusion surrounding the demand and supply of aid, coupled with varying preferences for the donation of aid in cash or in kind among the public, can lead to inefficiencies and delays in providing crucial assistance. The lessons learned from the unfortunate earthquake in Southeast Turkey and North of Syria in February 2023 highlighted the need for a comprehensive approach to address this issue.
This project is a sub-component of a larger umbrella project that seeks to comprehensively investigate the challenges of aid coordination and distribution during a disaster, focusing on Turkey’s February 6th Earthquake as the case study. The umbrella project aims to shed light on the communication and coordination between the major stakeholders in a disaster, i.e., the victims or beneficiaries, individual and corporate donors, volunteers, Humanitarian NGOs and the local and national government agencies. The expected outcome of the umbrella project is to provide training and instruction materials to the stakeholders to improve the coordination and communication in the provision and distribution of humanitarian aid. 
In this sub-project we aim to collect and analyze the voice of all the stakeholders in  disaster relief operations, using questionnaires, surveys, and interviews. We focus on beneficiaries, individual and corporate donors, volunteers and NOGs, and governmental aid agencies and collect information using targeted survey questions or interviews to collect the voice of each stakeholder group. Then we statistically analyze the results and draw conclusions. 
Project Phases
This project will consist of several key phases:
a. Data Collection from Social Media

  • We will gather a large dataset of Social Media messages (Twitter, Instagram, Facebook, ...) posted during major hazard events. This data will include messages from individuals, organizations, and official sources related to aid efforts, requests, and offers.

b. Data Mining and Analysis

  • We will employ advanced data mining techniques to analyze the collected social media data. Our analysis will include:
    • Identifying patterns in how aid-related messages are shared.
    • Examining the sentiment and urgency associated with these messages.
    • Identifying influential accounts or communities involved in aid communication.

c. Insights and Recommendations

  • Based on the findings from the data analysis, we will develop insights into how aid coordination can be improved through more effective communication on Social Media Platforms.
  • We will propose recommendations and strategies for optimizing the demand and supply of aids in cash and kind during hazard times.

Expected Outcomes

  • A deeper understanding of how Social Media influences the coordination of aid during major hazards.
  • Insights that can inform the development of communication strategies and tools to enhance aid coordination.
  • Recommendations for stakeholders involved in disaster response and relief efforts to improve their communication and coordination strategies.

The successful execution of this sub-project will contribute to more efficient and effective aid coordination during major hazard events, potentially reducing human suffering and saving lives. Additionally, the knowledge gained from this project can serve as a valuable resource for disaster management agencies, NGOs, and governments in their efforts to respond to future crises.
By focusing on the communication dynamics of Twitter messaging during hazard times, this sub-project plays a crucial role in the larger umbrella project's mission to improve the overall response to disasters and humanitarian crises. Through data-driven insights and recommendations, we aim to pave the way for a more coordinated and efficient system of aid distribution, ultimately benefiting those in need.

Related Areas of Project: 
Computer Science and Engineering
Industrial Engineering
Business Analytics

About Project Supervisors

Altuğ Tanaltay (FENS)
Raha Akhavan Tabatabaei (SBS)