Fake Instagram Profile Collection for Authentication Research

Fake Instagram Profile Dataset contains labeled examples of fraudulent social media accounts. The dataset is sourced from Kaggle and categorized for topics like social networks and online safety. Its specific creation date, author, and size are not provided.

Use Cases

• Train binary classifiers to predict 'fake_profile' label from user profile features.
• Analyze correlations between profile attributes like 'bio_length' or 'post_count' and authenticity labels.
• Develop feature engineering pipelines for account verification using profile metadata.
• Benchmark anomaly detection algorithms on social network user data.

Strengths

• Dataset is explicitly labeled for the 'fake profile' classification problem.
• Platform tags indicate a focus on practical applications in online safety and authentication.

Limitations

• Unknown row count prevents assessment of statistical power for model training.
• Specific column names and data types are not provided, limiting immediate usability.
• Potential geographic or temporal bias is unverified due to missing provenance details.

Provenance

Source

Kaggle

Collection Method

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Time Range

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Freshness

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Geography

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