discourser

A Streamlit application for analyzing the influence of a core corpus of materials against another corpus.

• Python 3.10

Installation

1. Clone this repository
2. Create a virtual environment: python -m venv venv
3. Activate virtual environment: source venv/bin/activate (Linux/Mac) or venv\Scripts\activate (Windows)
4. Install dependencies: pip install -r requirements.txt

You can create a conda environment with:

conda create -n discourser python=3.10
conda activate discourser

Running the Application

streamlit run app.py

Usage

1. Project Setup: Create or load a project
2. Core Corpus: Upload CSV metadata + text files for influential texts
3. Target Corpus: Upload corpus to analyze for influence
4. Analysis:
5. Results:

Nb the 'save project' is just saving your core and target corpuses; you still need to initialize the embeddings and so on.

Data Format

CSV Metadata

Required columns: filename, title, author, date, source Optional columns: document_type

Text Files

• UTF-8 encoded .txt files
• Paragraphs separated by double blank lines
• Filename must match CSV metadata

graph TD
A[Project Setup] --> B[Core Corpus Upload]
A --> C[Target Corpus Upload]
B --> D[Core Corpus Processing]
C --> E[Target Corpus Processing]
D --> F[Core Embeddings Generation]
E --> G[Target Embeddings Generation]
F --> H[Term Extraction from Core]
H --> I[Suggested Terms for Vectors]
F --> J[Core-Target Similarity Matrix]
G --> J
J --> K[Most Influential Core Texts]
I --> L[Custom Vector Creation]
F --> L
L --> M[Vector Projection Analysis]
F --> M
G --> M
M --> N[2D/3D Vector Spaces]
F --> O[Topic Modeling on Core]
O --> P[Topic-Target Analysis]
G --> P
J --> Q[Results & Visualization]
K --> Q
N --> Q
P --> Q
subgraph "Core Corpus Flow"
B
D
F
H
I
O
end
subgraph "Target Corpus Flow"
C
E
G
end
subgraph "Comparative Analysis"
J
K
M
N
P
end
subgraph "Vector Analysis"
L
M
N
end
style B fill:#e1f5fe
style C fill:#f3e5f5
style F fill:#e8f5e8
style G fill:#fff3e0
style J fill:#ffebee
style L fill:#f1f8e9
style O fill:#e0f2f1

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