Cross-Platform Digital Discourse Analysis of Iran: Topics, Sentiment, Polarization, and Event Validation on Telegram and Reddit
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arXiv
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| Format: | Preprint |
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2026
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| author | Antonakaki, Despoina Ioannidis, Sotiris |
| author_facet | Antonakaki, Despoina Ioannidis, Sotiris |
| contents | We analyze Iran-related discourse across two structurally different platforms: Telegram (7,567 messages from international news channels) and Reddit (23,909 posts and comments from Iran-focused and global communities). Using a single reproducible pipeline, we apply NMF topic modeling over TF--IDF features, VADER sentiment scoring, and a keyword-bundle escalation index capturing military, nuclear, and diplomatic narratives. To assess whether discourse dynamics track offline developments, we compare escalation time series with external protest and geopolitical event timelines using same-day and lagged correlation analysis. Same-day correlations are weak, but the strongest relationships occur at non-zero lags, consistent with anticipatory or reactive framing rather than instantaneous mirroring. Finally, using a separate real-time collection (February 2026), we observe synchronized increases in escalation-related narratives that coincide with documented geopolitical developments. Overall, the results show systematic cross-platform differences in narrative structure and tone, and provide quantitative evidence that online escalation signals can align with real-world developments with measurable temporal offsets. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_11057 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Cross-Platform Digital Discourse Analysis of Iran: Topics, Sentiment, Polarization, and Event Validation on Telegram and Reddit Antonakaki, Despoina Ioannidis, Sotiris Social and Information Networks We analyze Iran-related discourse across two structurally different platforms: Telegram (7,567 messages from international news channels) and Reddit (23,909 posts and comments from Iran-focused and global communities). Using a single reproducible pipeline, we apply NMF topic modeling over TF--IDF features, VADER sentiment scoring, and a keyword-bundle escalation index capturing military, nuclear, and diplomatic narratives. To assess whether discourse dynamics track offline developments, we compare escalation time series with external protest and geopolitical event timelines using same-day and lagged correlation analysis. Same-day correlations are weak, but the strongest relationships occur at non-zero lags, consistent with anticipatory or reactive framing rather than instantaneous mirroring. Finally, using a separate real-time collection (February 2026), we observe synchronized increases in escalation-related narratives that coincide with documented geopolitical developments. Overall, the results show systematic cross-platform differences in narrative structure and tone, and provide quantitative evidence that online escalation signals can align with real-world developments with measurable temporal offsets. |
| title | Cross-Platform Digital Discourse Analysis of Iran: Topics, Sentiment, Polarization, and Event Validation on Telegram and Reddit |
| topic | Social and Information Networks |
| url | https://arxiv.org/abs/2603.11057 |