Israel-Hamas war through Telegram, Reddit and Twitter
Despoina Antonakaki, Sotiris Ioannidis
TL;DR
This study analyzes online discourse surrounding the Israel–Hamas conflict across Telegram, Twitter, and Reddit by compiling Telegram’s 125k messages (from 17 channels) and publicly available Twitter (2001 tweets) and Reddit (over 2 million opinions) datasets. It applies volume analysis, entity extraction, and topic modeling via Latent Dirichlet Allocation (LDA) and BERTopic, followed by sentiment analysis to reveal polarized narratives and emotion-laden discussions. Key findings show strong platform polarization, with topics ranging from humanitarian concerns to military operations, and a measurable relationship between sentiment and topic prevalence that suggests propaganda dynamics. The work highlights Telegram’s role as a major, highly curated arena for conflict discourse, discusses implications for misinformation and governance, and provides a reproducible, cross-platform framework for analyzing social-media discourse during geopolitical crises.
Abstract
The Israeli-Palestinian conflict started on 7 October 2023, have resulted thus far to over 48,000 people killed including more than 17,000 children with a majority from Gaza, more than 30,000 people injured, over 10,000 missing, and over 1 million people displaced, fleeing conflict zones. The infrastructure damage includes the 87\% of housing units, 80\% of public buildings and 60\% of cropland 17 out of 36 hospitals, 68\% of road networks and 87\% of school buildings damaged. This conflict has as well launched an online discussion across various social media platforms. Telegram was no exception due to its encrypted communication and highly involved audience. The current study will cover an analysis of the related discussion in relation to different participants of the conflict and sentiment represented in those discussion. To this end, we prepared a dataset of 125K messages shared on channels in Telegram spanning from 23 October 2025 until today. Additionally, we apply the same analysis in two publicly available datasets from Twitter containing 2001 tweets and from Reddit containing 2M opinions. We apply a volume analysis across the three datasets, entity extraction and then proceed to BERT topic analysis in order to extract common themes or topics. Next, we apply sentiment analysis to analyze the emotional tone of the discussions. Our findings hint at polarized narratives as the hallmark of how political factions and outsiders mold public opinion. We also analyze the sentiment-topic prevalence relationship, detailing the trends that may show manipulation and attempts of propaganda by the involved parties. This will give a better understanding of the online discourse on the Israel-Palestine conflict and contribute to the knowledge on the dynamics of social media communication during geopolitical crises.