Upload README.md

README.md

@@ -1,109 +1,130 @@
+---
+title: E&C Model Interactive Platform
+emoji: 🧠
+colorFrom: indigo
+colorTo: blue
+sdk: gradio
+sdk_version: "3.44.0"
+app_file: app.py
+pinned: false
+---
+
 # 🧠 E&C Model Interactive Platform  
-## Entrenchment & Conventionalization Visual Demonstration
+### Entrenchment & Conventionalization Visual Demonstration
 
-This HuggingFace Space provides an interactive visualization of **Hans-Jörg Schmid’s Entrenchment & Conventionalization (E&C) Model**.  
-It allows users to explore how **individual cognitive processes (Entrenchment)** and **community-level linguistic diffusion (Conventionalization)** jointly shape language usage patterns.
+This Space provides an interactive visualization of **Hans-Jörg Schmid’s Entrenchment & Conventionalization (E&C) Model**, showing how **individual cognition (Entrenchment)** and **community diffusion (Conventionalization)** jointly shape linguistic behavior.
 
 ---
 
 # 🌟 Features
 
 ### 🔹 1. Single-Expression Analysis  
-Input any expression (e.g., *kind of*, *内卷*, *sort of*) and view:
+Enter any expression (e.g., *kind of*, *内卷*, *sort of*) to visualize:
 
-- Entrenchment curve (E)
-- Conventionalization curve (C)
-- Frequency-driven curve shapes
-- Linguistic explanations
-- Automated summary based on E&C theory
+- Entrenchment curve (E)  
+- Conventionalization curve (C)  
+- Frequency-driven curve transformation  
+- Automatic linguistic explanation  
+- Summary based on Schmid’s E&C theory  
 
 ---
 
 ### 🔹 2. Two-Expression Comparison  
-Compare two expressions (e.g., *kind of* vs *sort of*):
+Compare two expressions:
 
-- Entrenchment curves overlay
-- Conventionalization curves overlay
-- Heatmap showing E-curve differences
-- Automatic expert interpretation:
-  - Cognitive automation differences  
-  - Community adoption differences  
-  - Frequency-based explanations  
+- Overlaid Entrenchment curves  
+- Overlaid Conventionalization curves  
+- E-curve heatmap difference  
+- Auto-generated expert interpretation  
+
+This helps visualize how **usage frequency** affects cognitive automation and social adoption.
 
 ---
 
-### 🔹 3. Visualizations Included
-- Sigmoid-based Entrenchment model
-- Logistic-based Conventionalization model
-- Normalized heatmaps for differential processing
-- Styled card-based UI with gradient background
+# 📊 Visual Components
 
-> 📌 Note: The platform uses **mock frequencies** internally to ensure stable execution on HuggingFace.  
-A real-corpus version (Wikipedia, BookCorpus, OSCAR, etc.) is available upon request.
+- Sigmoid-shaped Entrenchment curves  
+- Logistic adoption curves for Conventionalization  
+- Heatmap showing differential entrenchment  
+- Clean card-style UI with gradient background  
 
----
+> **Note**: The current version uses *mock frequencies* for stable execution.  
+A real-corpus version (Wikipedia/BookCorpus/OSCAR) can be added later.
 
-# 📸 Screenshot (示意图占位符)
+---
 
-> *You can upload your Space screenshot here later.*
+# 📸 Screenshot (Optional)
+Add your screenshot here in the future:
 
+```
+[ Insert Screenshot Here ]
+```
 
 ---
 
 # 🎯 Purpose
 
-This interactive tool is designed for:
+This app is designed for:
 
-- Linguistics coursework
-- Cognitive linguistics demonstrations
-- Usage-based grammar exploration
-- Research visualization
-- Educational presentations
-- Translation and pragmatic analysis
+- Cognitive linguistics courses  
+- Usage-based grammar visualization  
+- Pragmatics & discourse analysis  
+- Translation studies  
+- Educational presentations  
+- Linguistic research demonstrations  
 
-It helps users understand how **usage frequency drives linguistic stability**, aligning with Schmid’s E&C Model.
+It shows how **usage → entrenchment → conventionalization → linguistic stability**.
 
 ---
 
 # 🛠️ Tech Stack
 
-- **Python**
-- **Gradio (3.x)** — fully compatible with Spaces
-- **Matplotlib** — visual plotting
-- **NumPy** — curve generation
-- **Custom CSS** — card UI & gradient background
+- Python  
+- Gradio 3.x  
+- Matplotlib  
+- NumPy  
+- Custom CSS  
 
 ---
 
 # 📁 File Structure
-|-- app.py # Main application
-|-- requirements.txt # Dependencies
-|-- README.md # Project description (this file)
 
+```
+app.py              # Main Gradio application
+requirements.txt    # Dependencies
+README.md           # This documentation
+```
 
-# 📘 Theoretical Background
+(Optional future files)
 
-### **Entrenchment (E)**  
-- Individual-level cognitive strengthening  
-- Frequent expressions → more automatic  
-- Steeper E-curves represent stronger entrenchment  
+```
+data/
+    word_freq.csv   # Optional: real corpus frequencies
+```
 
-### **Conventionalization (C)**  
-- Community-level diffusion  
-- Widespread usage → social norming  
-- Faster adoption → earlier sigmoid rise  
+---
+
+# 📘 Theory: E&C Model Overview
+
+### **Entrenchment (E)** — Individual level  
+- Increased automaticity through repeated use  
+- Higher frequency → steeper curve  
 
-### **E&C Dynamic Loop**  
-Schmid proposes that:
+### **Conventionalization (C)** — Community level  
+- Social diffusion and shared acceptance  
+- Faster rise → quicker normalization  
 
-> **E (individual repetition) reinforces C (social acceptance), and vice versa**,  
-> forming a *self-energizing feedback loop* that stabilizes linguistic structures.
+### **Dynamic Loop**  
+According to Schmid:
 
-This tool visualizes that mechanism directly.
+> **Individual repetition strengthens social convention;  
+> social convention increases repetition.**  
+
+This feedback loop stabilizes linguistic structures.
 
 ---
 
-# 📚 References
+# 📚 Reference
 
 Schmid, H.-J. (2020).  
 **The Dynamics of the Linguistic System: Usage, Conventionalization, and Entrenchment.**  
@@ -111,20 +132,17 @@ Oxford University Press.
 
 ---
 
-# 🚀 Future Extensions (可选待开发功能)
-
-- Real-corpus frequency mode (Wikipedia, CC100, OSCAR)
-- Google Ngram-based historical adoption curves
-- Collostructional analysis integration
-- Semantic embedding–based similarity comparison
-- Interactive diffusion simulation (“language evolution game”)
+# 🚀 Future Extensions
 
-If you'd like these features added, feel free to ask!
+- Real-corpus frequency mode  
+- Historical diffusion curves (Google Ngram)  
+- Collostruction analysis  
+- Semantic similarity comparison  
+- Language evolution simulation  
 
 ---
 
 # ❤️ Acknowledgements
 
-This space was created to support linguistic visualization, cognitive linguistics education, and usage-based theory demonstration.  
-Thanks for using this project!
-
+This tool was created for linguistic visualization, cognitive linguistics education, and research demonstration.  
+Thank you for exploring the E&C Model Interactive Platform!