Narrative Analysis of the July Revolution

What this is

A research project examining how media narratives shifted during and after Bangladesh’s July Revolution. The dataset is, to my knowledge, the largest collection of news articles on the topic. The analysis covers temporal patterns: how language changed week to week, how different newspapers diverged in framing, and where mainstream coverage parted ways with social media.

What’s in the dataset

News articles scraped from major Bangladeshi outlets, normalized and tagged with publication date, source, and metadata sufficient for cross-source comparison. Coverage spans the lead-up, the events themselves, and the aftermath.

What the analysis shows

Three threads I found most interesting:

1. Stance shifts within the same outlet over time. Specific newspapers changed framing partway through the period, in ways visible in word choice and headline structure.
2. Mainstream vs social media gap. Topics that dominated social media coverage often arrived in mainstream reporting later, or framed differently, or not at all.
3. Temporal clustering. Coverage volume around specific events was unevenly distributed across outlets in ways that suggest editorial decisions rather than news flow.

Why this exists

The July Revolution is recent enough that primary-source narrative analysis still matters for the historical record. Datasets compiled close to events tend to be more honest than ones reconstructed later. I built this because I wanted it to exist.

The slide deck linked above walks through the methodology, the dataset structure, and the key findings.