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Text Analysis

🔍 An advanced text analytics tool with intuitive visualization capabilities.

WindowsmacOSLinuxGitHub Last CommitContributorsGitHub License

🎬 Demo Video (Coming Soon!)

📋 Overview

Note

No Python or technical knowledge required! This tool is designed for everyone, regardless of programming experience.

Text Analysis provides researchers and analysts with powerful natural language processing capabilities, helping you uncover patterns and insights in text data. Particularly effective for analyzing:

  • Survey responses
  • Interview transcripts
  • Student feedback

✨ Features

  • Topic Modeling: Discover hidden themes in your text corpus using advanced algorithms
  • Word Cloud Visualization: Generate interactive visualizations of term frequency
  • Sentiment Analysis: Quantify emotional tone and polarity in text data
  • User-friendly Interface: Streamlit-based UI requiring no coding knowledge
  • uv Powered Setup: One-click installation that installs Python and all dependencies in seconds - no technical knowledge needed!

🔧 First Time Setup

Warning

Do not skip these steps if this is your first time using this application. It will not work without them.

Tip

Save the repository in a Projects/CEDA folder on your main drive for quick access.

1. Get the Repository

Option A: Clone with Git (or Github Desktop)

git clone https://github.com/cedanl/textanalysis.git
cd textanalysis

Option B: Download ZIP

Download Repository

After downloading extract the ZIP file and navigate into the folder.

2. Install uv Badge

MacOS & Linux (Terminal)

curl -LsSf https://astral.sh/uv/install.sh | sh

Windows (Powershell or Windows Terminal)

powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"

Close and reopen your terminal after installation.

Verify installation

uv self update

See the installation documentation for details and alternative installation methods.


🚀 Running the Application

Ready to see the magic happen? Your text analysis app is just one command away! ✨

First, get to the right spot:

Open a terminal in your textanalysis folder - it's super easy!

  • Windows: Shift + Right-click in folder → Open in Windows Terminal
  • Mac: Right-click folder → New Terminal at Folder
  • VS Code: Just click Terminal → New Terminal

Or simply navigate there:

cd path/to/textanalysis

Then, launch with a single command:

uv run streamlit run src/main.py

That's it! The app will automatically spring to life in your browser. If you've completed all the steps in the First Time Setup correctly, this is the only command you'll need going forward. 🎉

Pro Tip: Create a shortcut: .bat file (Windows) or .sh script (macOS/Linux)

Happy analyzing! ✨📊📝


🛠️ Built With

uv BadgeStreamlit BadgePython Badge

🤲 Support

If you find this project helpful, please consider:

  • ⭐ Starring the repo
  • 🐛 Reporting bugs
  • 💡 Suggesting features
  • 💻 Contributing code

If you encounter any issues or need further assistance, please feel free to open an issue or contact amir.khodaie@ru.nl

🙏 Acknowledgements

Special thanks to:

  • Amir Khodaie for starting the project and laying the foundation.
  • Ash Sewnandan & Tomer Iwan for elevating the project to professional standards by creating a complete, user-friendly application with a polished interface and robust architecture.
  • CEDA & Npuls for making this project possible by providing valuable resources and support.

🫂 Contributors

Thank you to all the people who have already contributed to textanalysis.

🚦 License

GitHub License

About

🚧 [IN DEVELOPMENT] - Text Analysis Streamlit Dashboard (Local). ⚡ Runs with uv

Resources

Readme
EUPL-1.2 license
Activity
Custom properties

Stars

6 stars

Watchers

1 watching

Forks

2 forks
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Braille fonts
Text Analysis
🔍 An advanced text analytics tool with intuitive visualization capabilities.
WindowsmacOSLinuxGitHub Last CommitContributorsGitHub License
🎬 Demo Video (Coming Soon!)
📋 Overview
Note
No Python or technical knowledge required! This tool is designed for everyone, regardless of programming experience.
Text Analysis provides researchers and analysts with powerful natural language processing capabilities, helping you uncover patterns and insights in text data. Particularly effective for analyzing:
  • Survey responses
  • Interview transcripts
  • Student feedback
✨ Features
  • Topic Modeling: Discover hidden themes in your text corpus using advanced algorithms
  • Word Cloud Visualization: Generate interactive visualizations of term frequency
  • Sentiment Analysis: Quantify emotional tone and polarity in text data
  • User-friendly Interface: Streamlit-based UI requiring no coding knowledge
  • uv Powered Setup: One-click installation that installs Python and all dependencies in seconds - no technical knowledge needed!

🔧 First Time Setup
Warning
Do not skip these steps if this is your first time using this application. It will not work without them.
Tip
Save the repository in a Projects/CEDA folder on your main drive for quick access.
1. Get the Repository
Option A: Clone with Git (or Github Desktop)
git clone https://github.com/cedanl/textanalysis.git
cd textanalysis
Option B: Download ZIP
Download Repository
After downloading extract the ZIP file and navigate into the folder.
2. Install uv Badge
MacOS & Linux (Terminal)
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows (Powershell or Windows Terminal)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Close and reopen your terminal after installation.
Verify installation
uv self update
See the installation documentation for
details and alternative installation methods.

🚀 Running the Application
Ready to see the magic happen? Your text analysis app is just one command away! ✨
First, get to the right spot:
Open a terminal in your textanalysis folder - it's super easy!
  • Windows: Shift + Right-click in folder → Open in Windows Terminal
  • Mac: Right-click folder → New Terminal at Folder
  • VS Code: Just click Terminal → New Terminal
Or simply navigate there:
cd path/to/textanalysis
Then, launch with a single command:
uv run streamlit run src/main.py
That's it! The app will automatically spring to life in your browser. If you've completed all the steps in the First Time Setup correctly, this is the only command you'll need going forward. 🎉
Pro Tip: Create a shortcut: .bat file (Windows) or .sh script (macOS/Linux)
Happy analyzing! ✨📊📝

🛠️ Built With
uv BadgeStreamlit BadgePython Badge
🤲 Support
If you find this project helpful, please consider:
  • ⭐ Starring the repo
  • 🐛 Reporting bugs
  • 💡 Suggesting features
  • 💻 Contributing code
If you encounter any issues or need further assistance, please feel free to open an issue or contact amir.khodaie@ru.nl
🙏 Acknowledgements
Special thanks to:
  • Amir Khodaie for starting the project and laying the foundation.
  • Ash Sewnandan & Tomer Iwan for elevating the project to professional standards by creating a complete, user-friendly application with a polished interface and robust architecture.
  • CEDA & Npuls for making this project possible by providing valuable resources and support.
🫂 Contributors
Thank you to all the people who have already contributed to textanalysis.
🚦 License
GitHub License
About
🚧 [IN DEVELOPMENT] - Text Analysis Streamlit Dashboard (Local). ⚡ Runs with uv
Resources
Readme
EUPL-1.2 license
Activity
Custom properties
Stars
6 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Braille fonts
Text Analysis
🔍 An advanced text analytics tool with intuitive visualization capabilities.
WindowsmacOSLinuxGitHub Last CommitContributorsGitHub License
🎬 Demo Video (Coming Soon!)
📋 Overview
Note
No Python or technical knowledge required! This tool is designed for everyone, regardless of programming experience.
Text Analysis provides researchers and analysts with powerful natural language processing capabilities, helping you uncover patterns and insights in text data. Particularly effective for analyzing:
  • Survey responses
  • Interview transcripts
  • Student feedback
✨ Features
  • Topic Modeling: Discover hidden themes in your text corpus using advanced algorithms
  • Word Cloud Visualization: Generate interactive visualizations of term frequency
  • Sentiment Analysis: Quantify emotional tone and polarity in text data
  • User-friendly Interface: Streamlit-based UI requiring no coding knowledge
  • uv Powered Setup: One-click installation that installs Python and all dependencies in seconds - no technical knowledge needed!

🔧 First Time Setup
Warning
Do not skip these steps if this is your first time using this application. It will not work without them.
Tip
Save the repository in a Projects/CEDA folder on your main drive for quick access.
1. Get the Repository
Option A: Clone with Git (or Github Desktop)
git clone https://github.com/cedanl/textanalysis.git
cd textanalysis
Option B: Download ZIP
Download Repository
After downloading extract the ZIP file and navigate into the folder.
2. Install uv Badge
MacOS & Linux (Terminal)
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows (Powershell or Windows Terminal)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Close and reopen your terminal after installation.
Verify installation
uv self update
See the installation documentation for
details and alternative installation methods.

🚀 Running the Application
Ready to see the magic happen? Your text analysis app is just one command away! ✨
First, get to the right spot:
Open a terminal in your textanalysis folder - it's super easy!
  • Windows: Shift + Right-click in folder → Open in Windows Terminal
  • Mac: Right-click folder → New Terminal at Folder
  • VS Code: Just click Terminal → New Terminal
Or simply navigate there:
cd path/to/textanalysis
Then, launch with a single command:
uv run streamlit run src/main.py
That's it! The app will automatically spring to life in your browser. If you've completed all the steps in the First Time Setup correctly, this is the only command you'll need going forward. 🎉
Pro Tip: Create a shortcut: .bat file (Windows) or .sh script (macOS/Linux)
Happy analyzing! ✨📊📝

🛠️ Built With
uv BadgeStreamlit BadgePython Badge
🤲 Support
If you find this project helpful, please consider:
  • ⭐ Starring the repo
  • 🐛 Reporting bugs
  • 💡 Suggesting features
  • 💻 Contributing code
If you encounter any issues or need further assistance, please feel free to open an issue or contact amir.khodaie@ru.nl
🙏 Acknowledgements
Special thanks to:
  • Amir Khodaie for starting the project and laying the foundation.
  • Ash Sewnandan & Tomer Iwan for elevating the project to professional standards by creating a complete, user-friendly application with a polished interface and robust architecture.
  • CEDA & Npuls for making this project possible by providing valuable resources and support.
🫂 Contributors
Thank you to all the people who have already contributed to textanalysis.
🚦 License
GitHub License
About
🚧 [IN DEVELOPMENT] - Text Analysis Streamlit Dashboard (Local). ⚡ Runs with uv
Resources
Readme
EUPL-1.2 license
Activity
Custom properties
Stars
6 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Braille fonts
Text Analysis
🔍 An advanced text analytics tool with intuitive visualization capabilities.
WindowsmacOSLinuxGitHub Last CommitContributorsGitHub License
🎬 Demo Video (Coming Soon!)
📋 Overview
Note
No Python or technical knowledge required! This tool is designed for everyone, regardless of programming experience.
Text Analysis provides researchers and analysts with powerful natural language processing capabilities, helping you uncover patterns and insights in text data. Particularly effective for analyzing:
  • Survey responses
  • Interview transcripts
  • Student feedback
✨ Features
  • Topic Modeling: Discover hidden themes in your text corpus using advanced algorithms
  • Word Cloud Visualization: Generate interactive visualizations of term frequency
  • Sentiment Analysis: Quantify emotional tone and polarity in text data
  • User-friendly Interface: Streamlit-based UI requiring no coding knowledge
  • uv Powered Setup: One-click installation that installs Python and all dependencies in seconds - no technical knowledge needed!

🔧 First Time Setup
Warning
Do not skip these steps if this is your first time using this application. It will not work without them.
Tip
Save the repository in a Projects/CEDA folder on your main drive for quick access.
1. Get the Repository
Option A: Clone with Git (or Github Desktop)
git clone https://github.com/cedanl/textanalysis.git
cd textanalysis
Option B: Download ZIP
Download Repository
After downloading extract the ZIP file and navigate into the folder.
2. Install uv Badge
MacOS & Linux (Terminal)
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows (Powershell or Windows Terminal)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Close and reopen your terminal after installation.
Verify installation
uv self update
See the installation documentation for
details and alternative installation methods.

🚀 Running the Application
Ready to see the magic happen? Your text analysis app is just one command away! ✨
First, get to the right spot:
Open a terminal in your textanalysis folder - it's super easy!
  • Windows: Shift + Right-click in folder → Open in Windows Terminal
  • Mac: Right-click folder → New Terminal at Folder
  • VS Code: Just click Terminal → New Terminal
Or simply navigate there:
cd path/to/textanalysis
Then, launch with a single command:
uv run streamlit run src/main.py
That's it! The app will automatically spring to life in your browser. If you've completed all the steps in the First Time Setup correctly, this is the only command you'll need going forward. 🎉
Pro Tip: Create a shortcut: .bat file (Windows) or .sh script (macOS/Linux)
Happy analyzing! ✨📊📝

🛠️ Built With
uv BadgeStreamlit BadgePython Badge
🤲 Support
If you find this project helpful, please consider:
  • ⭐ Starring the repo
  • 🐛 Reporting bugs
  • 💡 Suggesting features
  • 💻 Contributing code
If you encounter any issues or need further assistance, please feel free to open an issue or contact amir.khodaie@ru.nl
🙏 Acknowledgements
Special thanks to:
  • Amir Khodaie for starting the project and laying the foundation.
  • Ash Sewnandan & Tomer Iwan for elevating the project to professional standards by creating a complete, user-friendly application with a polished interface and robust architecture.
  • CEDA & Npuls for making this project possible by providing valuable resources and support.
🫂 Contributors
Thank you to all the people who have already contributed to textanalysis.
🚦 License
GitHub License
About
🚧 [IN DEVELOPMENT] - Text Analysis Streamlit Dashboard (Local). ⚡ Runs with uv
Resources
Readme
EUPL-1.2 license
Activity
Custom properties
Stars
6 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
BranchesTags
Repository files navigation
Braille fonts
Text Analysis
🔍 An advanced text analytics tool with intuitive visualization capabilities.
WindowsmacOSLinuxGitHub Last CommitContributorsGitHub License
🎬 Demo Video (Coming Soon!)
📋 Overview
Note
No Python or technical knowledge required! This tool is designed for everyone, regardless of programming experience.
Text Analysis provides researchers and analysts with powerful natural language processing capabilities, helping you uncover patterns and insights in text data. Particularly effective for analyzing:
  • Survey responses
  • Interview transcripts
  • Student feedback
✨ Features
  • Topic Modeling: Discover hidden themes in your text corpus using advanced algorithms
  • Word Cloud Visualization: Generate interactive visualizations of term frequency
  • Sentiment Analysis: Quantify emotional tone and polarity in text data
  • User-friendly Interface: Streamlit-based UI requiring no coding knowledge
  • uv Powered Setup: One-click installation that installs Python and all dependencies in seconds - no technical knowledge needed!

🔧 First Time Setup
Warning
Do not skip these steps if this is your first time using this application. It will not work without them.
Tip
Save the repository in a Projects/CEDA folder on your main drive for quick access.
1. Get the Repository
Option A: Clone with Git (or Github Desktop)
git clone https://github.com/cedanl/textanalysis.git
cd textanalysis
Option B: Download ZIP
Download Repository
After downloading extract the ZIP file and navigate into the folder.
2. Install uv Badge
MacOS & Linux (Terminal)
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows (Powershell or Windows Terminal)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Close and reopen your terminal after installation.
Verify installation
uv self update
See the installation documentation for
details and alternative installation methods.

🚀 Running the Application
Ready to see the magic happen? Your text analysis app is just one command away! ✨
First, get to the right spot:
Open a terminal in your textanalysis folder - it's super easy!
  • Windows: Shift + Right-click in folder → Open in Windows Terminal
  • Mac: Right-click folder → New Terminal at Folder
  • VS Code: Just click Terminal → New Terminal
Or simply navigate there:
cd path/to/textanalysis
Then, launch with a single command:
uv run streamlit run src/main.py
That's it! The app will automatically spring to life in your browser. If you've completed all the steps in the First Time Setup correctly, this is the only command you'll need going forward. 🎉
Pro Tip: Create a shortcut: .bat file (Windows) or .sh script (macOS/Linux)
Happy analyzing! ✨📊📝

🛠️ Built With
uv BadgeStreamlit BadgePython Badge
🤲 Support
If you find this project helpful, please consider:
  • ⭐ Starring the repo
  • 🐛 Reporting bugs
  • 💡 Suggesting features
  • 💻 Contributing code
If you encounter any issues or need further assistance, please feel free to open an issue or contact amir.khodaie@ru.nl
🙏 Acknowledgements
Special thanks to:
  • Amir Khodaie for starting the project and laying the foundation.
  • Ash Sewnandan & Tomer Iwan for elevating the project to professional standards by creating a complete, user-friendly application with a polished interface and robust architecture.
  • CEDA & Npuls for making this project possible by providing valuable resources and support.
🫂 Contributors
Thank you to all the people who have already contributed to textanalysis.
🚦 License
GitHub License
About
🚧 [IN DEVELOPMENT] - Text Analysis Streamlit Dashboard (Local). ⚡ Runs with uv
Resources
Readme
EUPL-1.2 license
Activity
Custom properties
Stars
6 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Braille fonts
Text Analysis
🔍 An advanced text analytics tool with intuitive visualization capabilities.
WindowsmacOSLinuxGitHub Last CommitContributorsGitHub License
🎬 Demo Video (Coming Soon!)
📋 Overview
Note
No Python or technical knowledge required! This tool is designed for everyone, regardless of programming experience.
Text Analysis provides researchers and analysts with powerful natural language processing capabilities, helping you uncover patterns and insights in text data. Particularly effective for analyzing:
  • Survey responses
  • Interview transcripts
  • Student feedback
✨ Features
  • Topic Modeling: Discover hidden themes in your text corpus using advanced algorithms
  • Word Cloud Visualization: Generate interactive visualizations of term frequency
  • Sentiment Analysis: Quantify emotional tone and polarity in text data
  • User-friendly Interface: Streamlit-based UI requiring no coding knowledge
  • uv Powered Setup: One-click installation that installs Python and all dependencies in seconds - no technical knowledge needed!

🔧 First Time Setup
Warning
Do not skip these steps if this is your first time using this application. It will not work without them.
Tip
Save the repository in a Projects/CEDA folder on your main drive for quick access.
1. Get the Repository
Option A: Clone with Git (or Github Desktop)
git clone https://github.com/cedanl/textanalysis.git
cd textanalysis
Option B: Download ZIP
Download Repository
After downloading extract the ZIP file and navigate into the folder.
2. Install uv Badge
MacOS & Linux (Terminal)
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows (Powershell or Windows Terminal)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Close and reopen your terminal after installation.
Verify installation
uv self update
See the installation documentation for
details and alternative installation methods.

🚀 Running the Application
Ready to see the magic happen? Your text analysis app is just one command away! ✨
First, get to the right spot:
Open a terminal in your textanalysis folder - it's super easy!
  • Windows: Shift + Right-click in folder → Open in Windows Terminal
  • Mac: Right-click folder → New Terminal at Folder
  • VS Code: Just click Terminal → New Terminal
Or simply navigate there:
cd path/to/textanalysis
Then, launch with a single command:
uv run streamlit run src/main.py
That's it! The app will automatically spring to life in your browser. If you've completed all the steps in the First Time Setup correctly, this is the only command you'll need going forward. 🎉
Pro Tip: Create a shortcut: .bat file (Windows) or .sh script (macOS/Linux)
Happy analyzing! ✨📊📝

🛠️ Built With
uv BadgeStreamlit BadgePython Badge
🤲 Support
If you find this project helpful, please consider:
  • ⭐ Starring the repo
  • 🐛 Reporting bugs
  • 💡 Suggesting features
  • 💻 Contributing code
If you encounter any issues or need further assistance, please feel free to open an issue or contact amir.khodaie@ru.nl
🙏 Acknowledgements
Special thanks to:
  • Amir Khodaie for starting the project and laying the foundation.
  • Ash Sewnandan & Tomer Iwan for elevating the project to professional standards by creating a complete, user-friendly application with a polished interface and robust architecture.
  • CEDA & Npuls for making this project possible by providing valuable resources and support.
🫂 Contributors
Thank you to all the people who have already contributed to textanalysis.
🚦 License
GitHub License
About
🚧 [IN DEVELOPMENT] - Text Analysis Streamlit Dashboard (Local). ⚡ Runs with uv
Resources
Readme
EUPL-1.2 license
Activity
Custom properties
Stars
6 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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Repository files navigation
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Text Analysis
🔍 An advanced text analytics tool with intuitive visualization capabilities.
WindowsmacOSLinuxGitHub Last CommitContributorsGitHub License
🎬 Demo Video (Coming Soon!)
📋 Overview
Note
No Python or technical knowledge required! This tool is designed for everyone, regardless of programming experience.
Text Analysis provides researchers and analysts with powerful natural language processing capabilities, helping you uncover patterns and insights in text data. Particularly effective for analyzing:
  • Survey responses
  • Interview transcripts
  • Student feedback
✨ Features
  • Topic Modeling: Discover hidden themes in your text corpus using advanced algorithms
  • Word Cloud Visualization: Generate interactive visualizations of term frequency
  • Sentiment Analysis: Quantify emotional tone and polarity in text data
  • User-friendly Interface: Streamlit-based UI requiring no coding knowledge
  • uv Powered Setup: One-click installation that installs Python and all dependencies in seconds - no technical knowledge needed!

🔧 First Time Setup
Warning
Do not skip these steps if this is your first time using this application. It will not work without them.
Tip
Save the repository in a Projects/CEDA folder on your main drive for quick access.
1. Get the Repository
Option A: Clone with Git (or Github Desktop)
git clone https://github.com/cedanl/textanalysis.git
cd textanalysis
Option B: Download ZIP
Download Repository
After downloading extract the ZIP file and navigate into the folder.
2. Install uv Badge
MacOS & Linux (Terminal)
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows (Powershell or Windows Terminal)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Close and reopen your terminal after installation.
Verify installation
uv self update
See the installation documentation for
details and alternative installation methods.

🚀 Running the Application
Ready to see the magic happen? Your text analysis app is just one command away! ✨
First, get to the right spot:
Open a terminal in your textanalysis folder - it's super easy!
  • Windows: Shift + Right-click in folder → Open in Windows Terminal
  • Mac: Right-click folder → New Terminal at Folder
  • VS Code: Just click Terminal → New Terminal
Or simply navigate there:
cd path/to/textanalysis
Then, launch with a single command:
uv run streamlit run src/main.py
That's it! The app will automatically spring to life in your browser. If you've completed all the steps in the First Time Setup correctly, this is the only command you'll need going forward. 🎉
Pro Tip: Create a shortcut: .bat file (Windows) or .sh script (macOS/Linux)
Happy analyzing! ✨📊📝

🛠️ Built With
uv BadgeStreamlit BadgePython Badge
🤲 Support
If you find this project helpful, please consider:
  • ⭐ Starring the repo
  • 🐛 Reporting bugs
  • 💡 Suggesting features
  • 💻 Contributing code
If you encounter any issues or need further assistance, please feel free to open an issue or contact amir.khodaie@ru.nl
🙏 Acknowledgements
Special thanks to:
  • Amir Khodaie for starting the project and laying the foundation.
  • Ash Sewnandan & Tomer Iwan for elevating the project to professional standards by creating a complete, user-friendly application with a polished interface and robust architecture.
  • CEDA & Npuls for making this project possible by providing valuable resources and support.
🫂 Contributors
Thank you to all the people who have already contributed to textanalysis.
🚦 License
GitHub License
About
🚧 [IN DEVELOPMENT] - Text Analysis Streamlit Dashboard (Local). ⚡ Runs with uv
Resources
Readme
EUPL-1.2 license
Activity
Custom properties
Stars
6 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

Skip to content
BranchesTags
Repository files navigation
Braille fonts
Text Analysis
🔍 An advanced text analytics tool with intuitive visualization capabilities.
WindowsmacOSLinuxGitHub Last CommitContributorsGitHub License
🎬 Demo Video (Coming Soon!)
📋 Overview
Note
No Python or technical knowledge required! This tool is designed for everyone, regardless of programming experience.
Text Analysis provides researchers and analysts with powerful natural language processing capabilities, helping you uncover patterns and insights in text data. Particularly effective for analyzing:
  • Survey responses
  • Interview transcripts
  • Student feedback
✨ Features
  • Topic Modeling: Discover hidden themes in your text corpus using advanced algorithms
  • Word Cloud Visualization: Generate interactive visualizations of term frequency
  • Sentiment Analysis: Quantify emotional tone and polarity in text data
  • User-friendly Interface: Streamlit-based UI requiring no coding knowledge
  • uv Powered Setup: One-click installation that installs Python and all dependencies in seconds - no technical knowledge needed!

🔧 First Time Setup
Warning
Do not skip these steps if this is your first time using this application. It will not work without them.
Tip
Save the repository in a Projects/CEDA folder on your main drive for quick access.
1. Get the Repository
Option A: Clone with Git (or Github Desktop)
git clone https://github.com/cedanl/textanalysis.git
cd textanalysis
Option B: Download ZIP
Download Repository
After downloading extract the ZIP file and navigate into the folder.
2. Install uv Badge
MacOS & Linux (Terminal)
curl -LsSf https://astral.sh/uv/install.sh | sh
Windows (Powershell or Windows Terminal)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
Close and reopen your terminal after installation.
Verify installation
uv self update
See the installation documentation for
details and alternative installation methods.

🚀 Running the Application
Ready to see the magic happen? Your text analysis app is just one command away! ✨
First, get to the right spot:
Open a terminal in your textanalysis folder - it's super easy!
  • Windows: Shift + Right-click in folder → Open in Windows Terminal
  • Mac: Right-click folder → New Terminal at Folder
  • VS Code: Just click Terminal → New Terminal
Or simply navigate there:
cd path/to/textanalysis
Then, launch with a single command:
uv run streamlit run src/main.py
That's it! The app will automatically spring to life in your browser. If you've completed all the steps in the First Time Setup correctly, this is the only command you'll need going forward. 🎉
Pro Tip: Create a shortcut: .bat file (Windows) or .sh script (macOS/Linux)
Happy analyzing! ✨📊📝

🛠️ Built With
uv BadgeStreamlit BadgePython Badge
🤲 Support
If you find this project helpful, please consider:
  • ⭐ Starring the repo
  • 🐛 Reporting bugs
  • 💡 Suggesting features
  • 💻 Contributing code
If you encounter any issues or need further assistance, please feel free to open an issue or contact amir.khodaie@ru.nl
🙏 Acknowledgements
Special thanks to:
  • Amir Khodaie for starting the project and laying the foundation.
  • Ash Sewnandan & Tomer Iwan for elevating the project to professional standards by creating a complete, user-friendly application with a polished interface and robust architecture.
  • CEDA & Npuls for making this project possible by providing valuable resources and support.
🫂 Contributors
Thank you to all the people who have already contributed to textanalysis.
🚦 License
GitHub License
About
🚧 [IN DEVELOPMENT] - Text Analysis Streamlit Dashboard (Local). ⚡ Runs with uv
Resources
Readme
EUPL-1.2 license
Activity
Custom properties
Stars
6 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages