funding-trend-forecaster

name	funding-trend-forecaster
description	Predict funding trend shifts using NLP analysis of grant abstracts from NIH, NSF, and Horizon Europe
version	1.0.0
category	Grant
tags	[]
author	AIPOCH
license	MIT
status	Draft
risk_level	High
skill_type	Hybrid (Tool/Script + Network/API)
owner	AIPOCH
reviewer
last_updated	2026-02-06

Skill: Funding Trend Forecaster

ID: 200
Version: 1.0.0
Author: OpenClaw Agent
License: MIT

---

Overview

Funding Trend Forecaster is an intelligent analysis tool that uses Natural Language Processing (NLP) technology to analyze awarded project abstracts from major global research funding agencies (NIH, NSF, Horizon Europe) and predict funding preference shift trends for the next 3-5 years.

Features

• Multi-source Data Collection: Automatically fetches awarded project data from NIH, NSF, Horizon Europe
• NLP Deep Analysis: Uses advanced text mining techniques to extract topics, keywords, and research trends
• Trend Prediction Model: Predicts funding direction changes based on time series analysis and topic modeling
• Visualized Reports: Generates charts and trend reports for intuitive display of analysis results
• Field Segmentation: Categorized analysis by medicine, engineering, natural sciences, and other fields

Installation

# Enter skill directory
cd skills/funding-trend-forecaster

# Install dependencies
pip install -r requirements.txt

# Download NLTK data
python -c "import nltk; nltk.download('punkt'); nltk.download('stopwords'); nltk.download('wordnet')"

Dependencies

requests>=2.28.0
beautifulsoup4>=4.11.0
pandas>=1.5.0
numpy>=1.23.0
scikit-learn>=1.1.0
textblob>=0.17.1
nltk>=3.7
matplotlib>=3.6.0
seaborn>=0.12.0
wordcloud>=1.8.0
python-dateutil>=2.8.0

Usage

Command Line Interface

# Run full analysis workflow
python scripts/main.py --analyze-all --output report.json

# Analyze specific agency only
python scripts/main.py --source nih --months 6

# Generate visualization report
python scripts/main.py --visualize --input data.json --output charts/

# View trend forecast
python scripts/main.py --forecast --years 5 --output forecast.json

API Call

from scripts.main import FundingTrendForecaster


forecaster = FundingTrendForecaster()


forecaster.collect_data(sources=[, , ], months=)


results = forecaster.analyze_trends()


forecast = forecaster.predict_trends(years=)


forecaster.export_report(output_path=, =)