Create README.md

README.md

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+---
+license: cc-by-4.0
+tags:
+- text
+- news
+- global
+- knowledge-graph
+- geopolitics
+dataset_info:
+  features:
+  - name: GKGRECORDID
+    dtype: string
+  - name: DATE
+    dtype: string
+  - name: SourceCollectionIdentifier
+    dtype: string
+  - name: SourceCommonName
+    dtype: string
+  - name: DocumentIdentifier
+    dtype: string
+  - name: V1Counts
+    dtype: string
+  - name: V2.1Counts
+    dtype: string
+  - name: V1Themes
+    dtype: string
+  - name: V2EnhancedThemes
+    dtype: string
+  - name: V1Locations
+    dtype: string
+  - name: V2EnhancedLocations
+    dtype: string
+  - name: V1Persons
+    dtype: string
+  - name: V2EnhancedPersons
+    dtype: string
+  - name: V1Organizations
+    dtype: string
+  - name: V2EnhancedOrganizations
+    dtype: string
+  - name: V1.5Tone
+    dtype: string
+  - name: V2.1EnhancedDates
+    dtype: string
+  - name: V2GCAM
+    dtype: string
+  - name: V2.1SharingImage
+    dtype: string
+  - name: V2.1Quotations
+    dtype: string
+  - name: V2.1AllNames
+    dtype: string
+  - name: V2.1Amounts
+    dtype: string
+  - name: tone
+    dtype: float64
+---
+
+# Dataset Card for dwb2023/gdelt-gkg-2025-v2
+
+## Dataset Details
+
+### Dataset Description
+
+This dataset contains GDELT Global Knowledge Graph (GKG) data covering February 2025. It captures global event interactions, actor relationships, and contextual narratives to support temporal, spatial, and thematic analysis.
+
+- **Curated by:** dwb2023
+
+### Dataset Sources
+
+- **Repository:** [http://data.gdeltproject.org/gdeltv2](http://data.gdeltproject.org/gdeltv2)
+- **GKG Documentation:** [GDELT 2.0 Overview](https://blog.gdeltproject.org/gdelt-2-0-our-global-world-in-realtime/), [GDELT GKG Codebook](http://data.gdeltproject.org/documentation/GDELT-Global_Knowledge_Graph_Codebook-V2.1.pdf)
+
+## Uses
+
+### Direct Use
+
+This dataset is suitable for:
+
+- Temporal analysis of global events
+
+### Out-of-Scope Use
+
+- Not designed for real-time monitoring due to its historic and static nature
+- Not intended for medical diagnosis or predictive health modeling
+
+## Dataset Structure
+
+### Features and Relationships
+
+- this dataset focuses on a subset of features from the source GDELT dataset.
+
+| Name | Type | Aspect | Description |
+|------|------|---------|-------------|
+| DATE | string | Metadata | Publication date of the article/document |
+| SourceCollectionIdentifier | string | Metadata | Unique identifier for the source collection |
+| SourceCommonName | string | Metadata | Common/display name of the source |
+| DocumentIdentifier | string | Metadata | Unique URL/identifier of the document |
+| V1Counts | string | Metrics | Original count mentions of numeric values |
+| V2.1Counts | string | Metrics | Enhanced numeric pattern extraction |
+| V1Themes | string | Classification | Original thematic categorization |
+| V2EnhancedThemes | string | Classification | Expanded theme taxonomy and classification |
+| V1Locations | string | Entities | Original geographic mentions |
+| V2EnhancedLocations | string | Entities | Enhanced location extraction with coordinates |
+| V1Persons | string | Entities | Original person name mentions |
+| V2EnhancedPersons | string | Entities | Enhanced person name extraction |
+| V1Organizations | string | Entities | Original organization mentions |
+| V2EnhancedOrganizations | string | Entities | Enhanced organization name extraction |
+| V1.5Tone | string | Sentiment | Original emotional tone scoring |
+| V2.1EnhancedDates | string | Temporal | Temporal reference extraction |
+| V2GCAM | string | Sentiment | Global Content Analysis Measures |
+| V2.1SharingImage | string | Content | URL of document image |
+| V2.1Quotations | string | Content | Direct quote extraction |
+| V2.1AllNames | string | Entities | Comprehensive named entity extraction |
+| V2.1Amounts | string | Metrics | Quantity and measurement extraction |
+
+### Aspects Overview:
+- **Metadata**: Core document information
+- **Metrics**: Numerical measurements and counts
+- **Classification**: Categorical and thematic analysis
+- **Entities**: Named entity recognition (locations, persons, organizations)
+- **Sentiment**: Emotional and tone analysis
+- **Temporal**: Time-related information
+- **Content**: Direct content extraction
+
+## Dataset Creation
+
+### Curation Rationale
+This dataset was curated to capture the rapidly evolving global narrative during February 2025. By zeroing in on this critical period, it offers a granular perspective on how geopolitical events, actor relationships, and thematic discussions shifted amid the escalating pandemic. The enhanced GKG features further enable advanced entity, sentiment, and thematic analysis, making it a valuable resource for studying the socio-political and economic impacts of emergent LLM capabilities.
+
+### Curation Approach
+A targeted subset of GDELT’s columns was selected to streamline analysis on key entities (locations, persons, organizations), thematic tags, and sentiment scores—core components of many knowledge-graph and text analytics workflows. This approach balances comprehensive coverage with manageable data size and performance. The ETL pipeline used to produce these transformations is documented here:
+[https://gist.github.com/donbr/5293468436a1a39bd2d9f4959cbd4923](https://gist.github.com/donbr/5293468436a1a39bd2d9f4959cbd4923).
+
+## Citation
+
+When using this dataset, please cite both the dataset and original GDELT project:
+
+```bibtex
+@misc{gdelt-gkg-2025-v2,
+    title = {GDELT Global Knowledge Graph 2025 Dataset},
+    author = {dwb2023},
+    year = {2025},
+    publisher = {Hugging Face},
+    url = {https://huggingface.co/datasets/dwb2023/gdelt-gkg-2025-v2}
+}
+```
+
+## Dataset Card Contact
+
+For questions and comments about this dataset card, please contact dwb2023 through the Hugging Face platform.