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Metaverse Blockchain Transaction Data
Crypto & Blockchain Transactions
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About
This dataset provides blockchain financial transactions within the Open Metaverse, designed to offer a rich, diverse, and realistic set of data for developing and testing anomaly detection models, fraud analysis, and predictive analytics in virtual environments. It captures various transaction types, user behaviours, and risk profiles across a global network. The Open Metaverse is an expansive, interoperable, and decentralised virtual space where blockchain technology is crucial for facilitating transactions, managing digital assets, and ensuring secure and transparent interactions. This dataset has been crafted to reflect the complexity and dynamism of blockchain activities within such an environment, serving as a foundational tool for research, development, and innovation in metaverse-related technologies.
Columns
The dataset includes 78,600 records, each representing a metaverse transaction.
- Timestamp: Date and time of the transaction, ranging from 1 January 2022 to 1 January 2023.
- Hour of Day: The hour part of the transaction timestamp, from 0 to 23.
- Sending Address: The blockchain address of the sender, with 1,161 unique values.
- Receiving Address: The blockchain address of the receiver, with 1,166 unique values.
- Amount: The transaction amount in a simulated currency, varying from 0.01 to 1,557.15.
- Transaction Type: Categorisation of the transaction, such as transfer, sale, purchase, scam, or phishing. There are 5 unique types, with 'sale' and 'purchase' being the most common.
- Location Region: The simulated geographical region of the transaction. There are 5 unique regions, including North America and Europe.
- IP Prefix: The simulated IP address prefix for the transaction, ranging from 10 to 192.
- Login Frequency: The frequency of login sessions by the user, which varies by age group, typically ranging from 1 to 8 logins.
- Session Duration: The duration of activity sessions in minutes, typically from 20 to 159 minutes.
- Purchase Pattern: The behavioural pattern of purchases, categorised as focused, random, or high-value. There are 3 unique patterns, with 'high_value' and 'random' being prevalent.
- Age Group: Categorisation of users based on their activity history into new, established, or veteran groups. There are 3 unique age groups.
- Risk Score: A calculated risk score based on transaction characteristics and user behaviour, ranging from 15 to 100.
- Anomaly: The risk level assessment for the transaction, classified as high_risk, moderate_risk, or low_risk. 'low_risk' accounts for 81% of records.
Distribution
The dataset is provided as a tabular data file, typically in CSV format, specifically
metaverse_transactions_dataset.csv, with a size of 14.83 MB. It contains 78,600 individual records, representing various metaverse transactions. The dataset is static and is not expected to be updated.Usage
This dataset is designed for a wide array of applications, including:
- Anomaly detection and fraud analysis within blockchain transactions.
- Behavioural modelling and predictive analytics concerning virtual economies.
- Research into secure and transparent digital asset management within the metaverse.
- Development and testing of algorithms for risk assessment and user verification.
Coverage
The dataset's scope encompasses blockchain financial transactions within a global network, with simulated geographical regions including North America and Europe. The time range of the transactions covers a full year, from 1 January 2022 to 1 January 2023. User demographics are categorised into 'new', 'established', and 'veteran' age groups, with login frequency varying across these segments.
License
Attribution 4.0 International (CC BY 4.0)
Who Can Use It
This dataset is intended for researchers, developers, and data scientists. Ideal users include those focused on:
- Creating and validating models for anomaly detection in digital transactions.
- Analysing and predicting fraudulent activities in virtual economies.
- Exploring mechanisms for secure and transparent digital asset management.
- Designing and implementing risk assessment algorithms and user verification systems.
- Individuals engaged in academic study or educational pursuits related to blockchain, metaverse, or financial analytics.
Dataset Name Suggestions
- Metaverse Blockchain Transaction Data
- Virtual Economy Fraud Detection Data
- Open Metaverse Financial Activity Log
- Blockchain Transaction Anomaly Records
- Digital Realm Financial Analytics Dataset
Attributes
Original Data Source: Metaverse Blockchain Transaction Data
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