Data: Network Graph Methodology

Summary: Network methodology outlines high-level aggregation of public interaction patterns without collecting personal private data [src:source-studies-indian-politics-2022].

Approach:

• Node set: Public accounts (official or media-recognized).
• Edge definition: Public retweet/reply/mention events aggregated.
• Weight: Frequency count within defined window.

Processing Steps:

1. Public dataset ingestion (rate-limited).
2. Filtering to verified/official-labeled accounts to avoid personal data handling.
3. Construction of weighted directed graph.

Metrics:

• In-degree centrality.
• Temporal modularity shifts during event windows.

Limitations: Excludes private groups or encrypted channels; not exhaustive of all interactions.

Independent Verification Path:

1. Sample small set of public interactions manually.
2. Reproduce edge list for limited time window.

References: Listed in sources.