Github: https://github.com/ShaliniAnandaPhD/HarmonyLens/tree/main
Project Plan: AI-Powered Conflict Resolution and Peacekeeping Assistant
Overview
HarmonyLens is an advanced AI system dedicated to understanding and resolving international conflicts. This plan serves as a guide to teach you how to utilize various tools and technologies integral to the system.
1. Communication Analysis
Objective
To analyze global communications for insights into sentiments, tones, and linguistic patterns that reflect underlying issues in conflicts.
Why and How
- Why: Understanding public sentiment and communication styles is crucial in conflict resolution.
How:
- Function
gather_data_from_apis():
- Use Social Media and News APIs to collect a diverse range of text data, including social media posts, news articles, and political speeches.
- Ensure data variety to capture a wide spectrum of public opinion and official communications.
- Function
preprocess_text_data(data) with NLTK:
- Process the collected data to make it suitable for analysis. This involves cleaning, tokenizing, removing stopwords, and normalizing text.
- Prepare data for more sophisticated analysis by breaking down complex sentences into analyzable elements.
- Function
perform_sentiment_analysis(data) with HuggingFace Transformers:
- Apply advanced NLP models, like BERT, to assess the sentiment of the processed text.
- Extract and quantify sentiments (positive, negative, neutral) from the data to gauge public mood and tone.
- Function
analyze_linguistic_patterns(data) with PyTorch:
- Use deep learning techniques to identify and analyze linguistic patterns and anomalies.
- Detect underlying themes and communication styles that are prevalent in the dataset.
Data Sources
Challenges and solutions:
12-25 - Shalini - Created modules
12-26 -