| --- |
| license: cc-by-nc-4.0 |
| pretty_name: "MELT: Memecoin Launch Trace" |
| language: |
| - en |
| tags: |
| - blockchain |
| - solana |
| - memecoin |
| - fraud-detection |
| - anomaly-detection |
| - behavioral-traces |
| task_categories: |
| - tabular-classification |
| size_categories: |
| - 100M<n<1B |
| configs: |
| - config_name: memecoin |
| data_files: memecoin/*.parquet |
| - config_name: pre_migration |
| data_files: transaction/pre_migration-*.parquet |
| - config_name: post_migration |
| data_files: transaction/post_migration-*.parquet |
| - config_name: bundle |
| data_files: bundle/*.parquet |
| - config_name: label |
| data_files: label/*.parquet |
| - config_name: feat |
| data_files: feat/feature.parquet |
| --- |
| |
| # MELT: A Behavioral Trace Dataset for High-Risk Memecoin Launch Detection |
|
|
| **MELT** (**ME**mecoin **L**aunch **T**race) is the first behavioral-trace dataset for |
| analyzing and detecting high-risk memecoin launches on Solana. It covers **41,470 memecoin |
| launches** issued through Pump.fun, with **200M+ on-chain transactions** parsed into typed |
| behavioral records, coordinated-account (bundle) traces, 122 engineered features, and |
| configurable risk-level annotations. |
|
|
| ## Dataset structure |
|
|
| The dataset is organized into six loadable configs: |
|
|
| | Config | Rows | Description | |
| |---|---|---| |
| | `memecoin` | 41,470 | One row per memecoin launch (metadata + timing). | |
| | `pre_migration` | ~30.8M | Pre-migration (bonding-curve) transactions, typed. | |
| | `post_migration` | ~187.7M | Post-migration (DEX) transactions, first hour after migration. | |
| | `bundle` | ~3.33M | Coordinated-behavior traces (Co-purchase / Fund-flow / Jito Bundle) linking an entity to a shared identifier. | |
| | `label` | 41,470 | Risk-level annotation per memecoin. | |
| | `feat` | 41,470 | 122 behavioral features per memecoin (five groups). | |
|
|
| `memecoin`, `label`, and `feat` share the same 41,470-memecoin population and can be joined |
| on the mint address. |
|
|
| ### `memecoin` |
| `mint_addr`, `creation_time`, `migrate_time`, `name`, `symbol`, `description`, `image_url`, |
| `twitter`, `website`, `telegram`, `signature`, `creator`. Times are UNIX seconds. |
|
|
| ### `pre_migration` / `post_migration` (transactions) |
| `mint`, `type` (`mint&swap` / `swap` / `transfer` / `zero`), `timestamp`, `signature`, |
| `trader_map` (**JSON string**: `{account: token_change}`), `token_amount`, `sol_amount`, |
| `fee_amount`, `price`, `block_slot`, `block_index`. |
|
|
| ### `bundle` |
| `entity`, `entity_type`, `identifier`, `source`. A single table of coordinated-behavior traces |
| across three sources; entities sharing an `identifier` within the same `source` are treated as |
| one coordinated group. The `entity_type` field distinguishes what `entity` holds per source: |
|
|
| | `source` | `entity_type` | `entity` | `identifier` | |
| |---|---|---|---| |
| | `Co-purchase` | `account` | trader account | co-purchase transaction signature | |
| | `Fund-flow` | `account` | trader account | common funder account | |
| | `Jito Bundle` | `signature` | transaction signature | Jito bundle id | |
|
|
| For the `Jito Bundle` source, transactions sharing a `bundle_id` (`identifier`) were submitted in |
| the same Jito bundle. |
|
|
| ### `label` |
| `mint_address`, `min_ratio`, `manipulated` (`yes` / `no` / empty), `label` |
| (`high` / `medium` / `low`). |
|
|
| ### `feat` |
| `mint_address`, `mint_ts`, and 122 features across five groups: `group1_*` (contextual), |
| `group2_*` (holding concentration), `group3_*` (market activity), `group4_*` (bundle |
| statistics), plus time-series fields `ts` / `ts_len`. All features are computed strictly |
| from pre-migration data to prevent label leakage (no label or return fields are included). |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| memecoin = load_dataset("Zinteck/MELT", "memecoin") |
| pre = load_dataset("Zinteck/MELT", "pre_migration") |
| post = load_dataset("Zinteck/MELT", "post_migration") |
| bundle = load_dataset("Zinteck/MELT", "bundle") |
| label = load_dataset("Zinteck/MELT", "label") |
| feat = load_dataset("Zinteck/MELT", "feat") |
| |
| # trader_map is a JSON string |
| import json |
| row = pre["train"][0] |
| traders = json.loads(row["trader_map"]) |
| ``` |
|
|
| ## License |
|
|
| This dataset is released under the **Creative Commons Attribution-NonCommercial 4.0 |
| International (CC BY-NC 4.0)** license. It is derived from public Solana on-chain data and is |
| intended for research and non-commercial use. |
|
|
| ## Citation |
|
|
| This dataset accompanies a paper under review. Citation details will be added upon |
| publication; please refer to the anonymized submission for now. |
|
|
