lstm_dataset/README.md

🕸 Ethereum Transaction Graph Dataset (GNN)

This dataset represents Ethereum transactions as edges between addresses.
It is designed for Graph Neural Networks (GNN), both static embeddings and temporal graph learning.
The dataset contains 2-hop graphs, i.e., it includes neighbors of neighbors for each address.

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📑 Contents

• edges_all/edges.parquet — all transactions (full edge list).
• edges_by_week/week=YYYY-Www/edges.parquet — weekly slices.
• edges_by_month/month=YYYY-MM/edges.parquet — monthly slices.
• meta/{week,month}_window_meta.parquet — time window ranges and statistics.
• labels/targets_global.parquet — labeled addresses (node_id, is_scam, is_contract, address).
• mapping/address_id_map_labels.parquet — (address, node_id) mapping.
• targets/{week,month}_targets.parquet — labeled nodes active in each window.

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🔑 Edge Schema

Field	Type	Units	Description
src_id	UInt64	—	Source node ID (hash of lowercase Ethereum address).
dst_id	UInt64	—	Destination node ID (hash of lowercase Ethereum address).
ts	Int64	seconds	Unix timestamp of the transaction (UTC).
value_wei	STRING	wei	Transaction value in wei (exact decimal stored as string).
tx_fee_wei	STRING	wei	Transaction fee in wei (exact decimal stored as string).
block_number	Int64	block	Ethereum block number of the transaction.
contract_creation	Bool	—	True if transaction created a smart contract.
tx_hash	STRING	hex	Unique transaction hash.

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Notes

• Transactions are not filtered: all edges included.
• Supervision: loss computed only on labeled addresses.
• Dynamic GNN: use edges_by_week/ or edges_by_month/.
• Static embeddings: use edges_all/edges.parquet.