Global Conflict Intelligence Dashboard

A hybrid conflict-monitoring dashboard built with Python, Streamlit, GDELT, and GitHub Actions to track recent war-related media signals and structured conflict patterns.

This project combines:

• a Recent War News Pulse powered by GDELT
• a Structured Conflict Dashboard powered by historical ACLED data
• an automated refresh pipeline that updates the processed datasets on a schedule

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Project Overview

The goal of this project is to build a visually polished and analytically useful dashboard for monitoring global conflict-related developments.

The dashboard is designed to support:

• recent war/news monitoring
• conflict topic tracking
• media-source analysis
• geographic conflict visualization
• historical structured conflict exploration

This project was built as a portfolio project connecting interests in:

• international studies
• data analytics
• Python development
• dashboard design
• automation workflows

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Key Features

Recent War News Pulse

This section uses GDELT to monitor recent conflict-related media coverage.

Features include:

• recent article count
• top source countries
• top domains
• language distribution
• conflict topic breakdown
• latest headlines table
• automatically generated summary insight box

Structured Conflict Dashboard

This section uses cleaned ACLED data for structured conflict analysis.

Features include:

• conflict event KPIs
• fatalities summary
• interactive conflict map
• event type breakdown
• daily event trend
• fatalities by region
• recent events table

Automation

The project includes an automated refresh workflow using GitHub Actions.

Automation covers:

• fetching new GDELT data
• cleaning and processing the raw file
• updating processed CSV files
• committing refreshed data back to the repository

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Screenshots

• Recent War News Pulse tab

- Structured Conflict Dashboard tab

Tech Stack

• Python
• Pandas
• Streamlit
• Plotly
• PyDeck
• GDELT DOC 2.0 API
• ACLED (historical structured conflict layer)
• GitHub Actions

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Project Structure

global-conflict-intelligence-dashboard/
│
├── data/
│   ├── raw/
│   └── processed/
│
├── src/
│   ├── fetch_data.py
│   ├── clean_data.py
│   ├── fetch_gdelt.py
│   ├── clean_gdelt.py
│   └── run_refresh_pipeline.py
│
├── .github/
│   └── workflows/
│       └── refresh_data.yml
│
├── app.py
├── requirements.txt
├── README.md
└── .gitignore

Data Sources

1. GDELT

GDELT is used for the recent war-news pulse layer.

It provides:

• article metadata
• source country
• language
• domain
• headline-level recent media coverage

This powers the recent/news-oriented side of the dashboard.

2. ACLED

ACLED is used for the structured conflict analysis layer.

It provides:

• conflict event records
• event types
• locations
• fatalities
• actors
• regional trends

In this project, ACLED is used primarily for historical structured exploration because recent detailed access depends on account access level.

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How the Dashboard Works

The dashboard is split into two tabs:

Tab 1 — Recent War News Pulse

This tab focuses on recent conflict-related media signals and includes:

• summary insight box
• recent article metrics
• topic breakdown
• top source countries
• language distribution
• top domains
• latest headlines

Tab 2 — Structured Conflict Dashboard

This tab focuses on conflict-event analytics and includes:

• event KPIs
• interactive map
• conflict event trends
• regional fatalities
• recent structured events

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Automation Workflow

The project includes a GitHub Actions workflow that refreshes the processed data automatically.

The refresh pipeline:

1. fetches recent GDELT war-news data
2. cleans and filters the raw data
3. saves processed CSV files
4. commits updated processed files back to the repository

This turns the project from a static dashboard into a lightweight monitoring system.

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How to Run Locally

1. Clone the repository

git clone https://github.com/Vireen555/global-conflict-intelligence-dashboard.git
cd global-conflict-intelligence-dashboard

2. Create and activate a virtual environment

Windows

python -m venv venv
venv\Scripts\activate

MAC/Linux

python -m venv venv
source venv/bin/activate

3. Install dependencies

pip install -r requirements.txt

4. Run the data pipeline manually

python src/fetch_gdelt.py
python src/clean_gdelt.py

If needed, you can also run:

python src/run_refresh_pipeline.py

5. Start the Streamlit app

streamlit run app.py

Current Capabilities

• recent conflict-news monitoring
• topic-based war-news analysis
• media-source distribution analysis
• automated processed-data refresh pipeline
• minimal glass-style dashboard UI

Limitations

• GDELT provides article/news metadata, not fully structured conflict-event records
• conflict topic detection is currently rule-based and can still include some noise
• ACLED recent detailed access depends on account access level
• article-level geolocation is not yet implemented in the recent news tab

These limitations also create future improvement opportunities.

Future Improvements

Planned and possible improvements include:

• more advanced topic classification
• better false-positive filtering
• sentiment or tone analysis
• clickable article cards
• region-based filtering for GDELT articles
• improved summary generation
• deployment on Streamlit Community Cloud
• optional React-based frontend version in the future

Why I Built This

I wanted to build a project that sits at the intersection of:

• global affairs
• international studies
• data analytics
• Python
• automation
• visual storytelling The idea was to create something that is not just technically functional, but also relevant to real-world ongoing events and useful as a portfolio showcase.

Author

Vireen Chowdary Vesangi

If you found this project interesting, feel free to connect or explore the repository.

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