Zoom Chat Analyzer

📊 Chat Analyzer is a Streamlit-based web application that allows you to analyze chat data from text files. It provides insights into the most active and silent participants in the chat.

🎯 Algoritma (algorit.ma) purposes.

Features

• 🔬 Analyze chat data from text files.
• 🔎 Identify the most active and silent participants.
• 📊 Visualize chat statistics with interactive plots.
• 📥 Copy chat data to clipboard or download as CSV.

How to Use

1. Upload Files:

   • Click on the "Choose File" button to upload one or multiple chat files. Supported file format: .txt.

2. Input Course Details:

   • Enter the course name and day information in the sidebar.

3. Analysis:

   • After uploading the file(s) and providing course details, the app will analyze the chat data.
   • It will display two plots:
     • Top 10 Most Active Participants.
     • Top 10 Most Silent Participants.
   • Additionally, the app will print the top 10 most active and silent participant names.

4. Data Summary:

   • Below the plots, you can find a summary of the chat data.
   • It includes timestamps, participants, and messages.

5. Copy or Download Data:

   • You can copy the chat data to your clipboard or download it as a CSV file.

6. Feedback:

   • We welcome your feedback! Feel free to reach out with any questions or suggestions.

Installation

To run this app locally, make sure you have Python installed. Then, follow these steps:

1. Clone this repository:

   git clone https://github.com/product-rnd/zoom-chat-analyzer.git
   

2. Navigate to the project directory:

   cd zoom-chat-analyzer
   

3. Install the required dependencies:

   pip install -r requirements.txt
   

4. Run the Streamlit app:

   streamlit run app.py
   

5. Access the app in your browser at http://localhost:8501.

Example Chat Data

You can use the provided example chat data file (GMT20240816.txt) to test the application. ⚠️ Ensure that the file names follow the format "GMT+DATE.txt" where "DATE" represents the date in any specific format.

00:24:39    [Instructor] Alexander Graham Bell:   sore Bu
00:33:28    [TA] Marie Curie:    Iya sama sama Bu
01:25:50    [TA] Leonardo da Vinci:    Selamat datang di kelas EDA Day 4, Yoda Night Online. Berikut pranala kelas yang perlu dipersiapkan:...
01:37:36    [TA] Albert Einstein:  😀
01:37:52    J. Robert Oppenheimer Zoom (Laptop):   Reacted to "😀" with 🤣
01:46:25    Issac Newton:    household_new[(household_new['year'] == 2018)]
01:46:47    [TA] J. Robert Oppenheimer:  Reacted to "household_new[(household..." with 👏
01:48:34    B. J. Habibie:    karena data household_new yang originalnya akan keoverwrite
01:48:40    Issac Newton:    data awalnya berubah
02:00:25    J. Robert Oppenheimer Zoom (Laptop):   minimarket total sales nya sangat mendominasi dibandingkan format penjualan yg lain
02:02:05    Roberto Mario Uta:   Reacted to "kalau gak makan nasi..." with 😂
02:02:05    Arthur Scherbius:   Reacted to "kalau gak makan nasi..." with 🤣

Credits

• Developed by RnD Product Team - Algoritma
• © 2024 Algoritma