---
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.