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A newer version of the Streamlit SDK is available: 1.41.1

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metadata
title: Social-Stat
emoji: 🦕
colorFrom: indigo
colorTo: pink
sdk: streamlit
sdk_version: 1.29.0
app_file: src/app.py
pinned: false

Social-Stat: A Streamlit Web App for Social Media Analysis

Streamlit web application for social network analysis.

Hugging Face Spaces

social-stat

Features

  • Emotion Prediction: Utilizes a text classification model to predict emotions in video comments.
  • Topic Modeling: Applies Non-negative Matrix Factorization (NMF) to identify and visualize the main topics discussed in the comments.
  • t-SNE Visualization: Provides a 2D and 3D visualization of the comment data, highlighting patterns and clusters.
  • Language Detection: Detects the language of comments to understand the global reach of the video and visualizes the distribution of languages on a plotly Choropleth map.

How to Use

  1. Enter a YouTube Video URL or ID: Input the URL or ID of the YouTube video.
  2. Select Analysis Options: Choose whether to predict emotions, perform NMF, visualize with t-SNE, and display a language map.
  3. Adjust Parameters: Customize the analysis by adjusting parameters such as the number of NMF components, t-SNE perplexity.
  4. Analyze: Click the "Analyze" button to start the analysis.

Installation and Running 

git clone https://github.com/molokhovdmitry/social-stat
python -m pip install --upgrade pip
pip install -r requirements.txt
streamlit run src/app.py