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README.md

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-license: mit
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+---
+license: mit
+task_categories:
+  - text-classification
+language:
+  - en
+size_categories:
+  - 100K<n<1M
+tags:
+  - deception-detection
+  - fake-news
+---
+
+This repository contains the **SEPSIS** dataset, introduced in the paper [SEPSIS: I Can Catch Your Lies -- A New Paradigm for Deception Detection](https://huggingface.co/papers/2312.00292).
+
+The SEPSIS dataset is a novel, large-scale annotated dataset designed for deception detection, specifically focusing on "lies of omission" using Natural Language Processing (NLP) techniques. It comprises **876,784 samples**, curated by amalgamating a popular large-scale fake news dataset and scraped news headlines from the Twitter handle of the Times of India.
+
+Each sample in the dataset is labeled with four distinct layers of annotation, providing a comprehensive understanding of deceptive content:
+*   **Type of omission**: Categorizes the type of omission into speculation, bias, distortion, sounds factual, and opinion.
+*   **Colors of lies**: Identifies the moral or ethical implications of the lie (e.g., black, white).
+*   **Intention of such lies**: Indicates the underlying purpose of the lie (e.g., to influence).
+*   **Topic of lies**: Specifies the subject matter of the deceptive content (e.g., political, educational, religious).
+
+This dataset aims to encourage further research in the field of deception detection and explores the intricate relationship between lies of omission and propaganda techniques.