Unveiling Communication and Support Dynamics: Analyzing Telegram and Helpline Data in Conflict Zones

Tiwari, Atharva

Student Work

Unveiling Communication and Support Dynamics: Analyzing Telegram and Helpline Data in Conflict Zones

Public Deposited

The traditional Fordist approach to humanitarian response often falls short in addressing the complexities of modern crises. To better understand the demands arising from the Ukrainian situation and suggest practical solutions, this project leverages the Telegram and 527 datasets. By conducting rigorous analysis, we aim to offer insights through the following approaches. (1) 527 Helpline Dataset Analysis: We employed Exploratory Data Analysis (EDA) and a regression model to understand the factors influencing the protection of Ukrainian rights abroad. The regression model helping identified key features impacting these protections. (2) Telegram Dataset Analysis: Using EDA and a Latent Dirichlet Allocation (LDA) machine learning model, we analyzed the Telegram dataset to uncover important themes and communication patterns. This analysis sheds lights on public debates and concerns. By integrating the findings from both datasets, this project aims to provide a comprehensive understanding of digital communication trends and practical support mechanisms. These insights have significant implications for future research on conflict-affected populations and international human rights efforts, offering a nuanced perspective on addressing modern humanitarian crises.

This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

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