Skip to content

Hierarchical Text-Image Cognitive Framework for Social Media: A Case Study on Scenic Spot Posts in RED

License

Notifications You must be signed in to change notification settings

BlackThompson/scenic_spot_analysis

Repository files navigation

Text-Image Cognitive Framework

License

Code for paper: "Hierarchical Text-Image Cognitive Framework for Social Media: A Case Study on Scenic Spot Posts in RED".

This paper proposed a Text-Image Cognitive Framework to simulate how people perceive scenic spots through RED posts. The framework uses advanced models to analyze images and text at different levels: image, post, and comprehensive. Comparing only pictures and only text, the framework achieves the highest scores regarding completeness and satisfaction.

framework

framework_formal

Usage

  1. Clone the repository:

    git clone https://github.com/BlackThompson/scenic_spot_analysis.git
    
  2. Create a new environment and install dependencies:

    • Python version should be >= 3.8.
    conda create --name cogframe python=3.8
    conda activate cogframe
    pip install -r requirements.txt
    
  3. You can find the main code of the framework in utils.py and run.ipynb.

About

Hierarchical Text-Image Cognitive Framework for Social Media: A Case Study on Scenic Spot Posts in RED

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published