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Merge branch 'fix/nuget-package-version' - ML.NET 5.0 upgrade
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‎CHANGELOG.md‎

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# Changelog
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All notable changes to this project will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [2.0.0] - 2026-01-22
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### Added
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- Multi-targeting support for `.NET Standard 2.0`, `.NET 8`, and `.NET 10`
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- Package README included in NuGet package
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- Additional package tags for better discoverability
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### Changed
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- **Upgraded ML.NET from 1.5.5 to 5.0.0** - This is a major dependency upgrade
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- Updated package description and metadata
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- Test project upgraded to .NET 8 with latest test framework versions
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### Compatibility
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This release maintains **full backward compatibility** with v1.x:
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- The API (`Sentiments.Predict(text)`) remains unchanged
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- The `SentimentPrediction` model is unchanged
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- Existing code will work without modifications
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### Migration Guide
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No code changes required. Simply update your package reference:
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```xml
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<!-- Before -->
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<PackageReference Include="SentimentAnalyzer" Version="1.2.3" />
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<!-- After -->
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<PackageReference Include="SentimentAnalyzer" Version="2.0.0" />
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```
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### Platform Support
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| Platform | Supported |
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|----------|-----------|
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| .NET Framework 4.6.1+ | ✅ (via netstandard2.0) |
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| .NET Core 2.0+ | ✅ (via netstandard2.0) |
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| .NET 5/6/7 | ✅ (via netstandard2.0) |
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| .NET 8 (LTS) | ✅ Native |
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| .NET 10 (LTS) | ✅ Native |
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| .NET MAUI | ✅ |
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| Blazor (Server/WASM) | ✅ |
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| Unity | ✅ (via netstandard2.0) |
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---
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## [1.2.3] - 2021-xx-xx
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### Changed
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- Performance improvements using singleton pattern
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- Based on ML.NET version 1.5.5
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## [1.0.0] - 2020-xx-xx
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### Added
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- Initial release
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- Binary sentiment analysis (positive/negative)
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- Offline, on-device prediction
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- Thread-safe singleton pattern

‎README.md‎

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# SentimentAnalyzer - On-device (offline) Sentiment Analysis for .NET Standard apps
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This is a library which can be used to consume a model which I created using ML.NET.
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For further information, you can always have a look at my [blog](https://www.arafattehsin.com/blog/sentimentanalyzer-ondevice-machine-learning/)
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## Quick Start
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```c#
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# SentimentAnalyzer
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[![NuGet](https://img.shields.io/nuget/v/SentimentAnalyzer.svg)](https://www.nuget.org/packages/SentimentAnalyzer/)
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[![NuGet Downloads](https://img.shields.io/nuget/dt/SentimentAnalyzer.svg)](https://www.nuget.org/packages/SentimentAnalyzer/)
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[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
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**On-device (offline) Sentiment Analysis for .NET applications**
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A cross-platform, privacy-first library for sentiment analysis that runs entirely on-device without requiring internet connectivity. Powered by [ML.NET 5.0](https://dot.net/ml).
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## ✨ Features
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- 🔒 **Privacy-first** - All processing happens on-device, no data leaves your app
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- 📴 **Fully offline** - No internet connection required
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- 🚀 **Cross-platform** - Works on .NET Standard 2.0, .NET 8, .NET 10, MAUI, Blazor, Unity
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- ⚡ **Fast** - Thread-safe singleton pattern for optimal performance
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- 📦 **Lightweight** - Single NuGet package, no external dependencies
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## 📦 Installation
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```bash
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dotnet add package SentimentAnalyzer
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```
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Or via Package Manager:
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```powershell
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Install-Package SentimentAnalyzer
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```
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## 🚀 Quick Start
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```csharp
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using SentimentAnalyzer;
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// Analyze sentiment
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var result = Sentiments.Predict("This product is amazing!");
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Console.WriteLine($"Sentiment: {(result.Prediction ? "Positive" : "Negative")}");
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Console.WriteLine($"Confidence: {result.Score:P2}");
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```
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## 📖 API Reference
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### `Sentiments.Predict(string text)`
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Analyzes the sentiment of the provided text.
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**Parameters:**
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- `text` - The text to analyze
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**Returns:** `SentimentPrediction`
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- `Prediction` (`bool`) - `true` for Positive sentiment, `false` for Negative sentiment
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- `Score` (`float`) - Confidence score (0.0 to 1.0)
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### Example Usage
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```csharp
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using SentimentAnalyzer;
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var sentiment = Sentiments.Predict("some string");
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// Positive sentiment
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var positive = Sentiments.Predict("I love this! Best purchase ever!");
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// positive.Prediction = true, positive.Score ≈ 0.95
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// Negative sentiment
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var negative = Sentiments.Predict("Terrible experience, very disappointed.");
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// negative.Prediction = false, negative.Score ≈ 0.12
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```
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## 🎯 Platform Support
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| Platform | Supported | Target Framework |
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| --------------------- | --------- | ---------------- |
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| .NET Framework 4.6.1+ | ✅ | netstandard2.0 |
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| .NET Core 2.0+ | ✅ | netstandard2.0 |
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| .NET 5/6/7 | ✅ | netstandard2.0 |
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| .NET 8 (LTS) | ✅ | net8.0 |
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| .NET 10 (LTS) | ✅ | net10.0 |
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| .NET MAUI | ✅ | All targets |
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| Blazor Server | ✅ | All targets |
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| Blazor WebAssembly | ✅ | netstandard2.0 |
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| Unity | ✅ | netstandard2.0 |
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## 📋 Use Cases
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- **Customer Feedback Analysis** - Automatically categorize reviews and feedback
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- **Social Media Monitoring** - Track brand sentiment in real-time
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- **Chatbot Intelligence** - Detect user mood and respond appropriately
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- **Content Moderation** - Flag negative or toxic content
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- **IoT/Edge Devices** - Run sentiment analysis on resource-constrained devices
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- **Air-gapped Environments** - Perfect for defense, healthcare, and enterprise use
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## 🔄 Migration from v1.x
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Version 2.0 maintains **full backward compatibility**. No code changes required:
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```xml
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<!-- Just update the version -->
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<PackageReference Include="SentimentAnalyzer" Version="2.0.0" />
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```
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`Predict` returns a `SentimentPrediction` which contains:
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See [CHANGELOG.md](CHANGELOG.md) for detailed release notes.
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## 📚 Learn More
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- [Blog Post: On-device Machine Learning with SentimentAnalyzer](https://www.arafattehsin.com/blog/sentimentanalyzer-ondevice-machine-learning/)
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- [ML.NET Documentation](https://docs.microsoft.com/dotnet/machine-learning/)
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## 📄 License
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This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
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## 🤝 Contributing
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- `Prediction` (`bool`) - `true` is Positive sentiment, `false` is Negative sentiment.
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- `Score` (`float`) - A score representing the model's accuracy
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Contributions are welcome! Please feel free to submit a Pull Request.

‎SentimentAnalyzer.Tests/SentimentAnalyzer.Tests.csproj‎

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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<TargetFramework>netcoreapp3.1</TargetFramework>
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<TargetFramework>net8.0</TargetFramework>
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<IsPackable>false</IsPackable>
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<LangVersion>latest</LangVersion>
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<Nullable>disable</Nullable>
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<ImplicitUsings>disable</ImplicitUsings>
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</PropertyGroup>
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</ItemGroup>
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<PackageReference Include="Microsoft.NET.Test.Sdk" Version="16.5.0" />
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<PackageReference Include="System.Text.Json" Version="5.0.1" />
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<PackageReference Include="xunit" Version="2.4.0" />
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<PackageReference Include="xunit.runner.visualstudio" Version="2.4.0" />
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<PackageReference Include="coverlet.collector" Version="1.2.0" />
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<PackageReference Include="Microsoft.NET.Test.Sdk" Version="17.11.1" />
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<PackageReference Include="System.Text.Json" Version="8.0.5" />
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<PackageReference Include="xunit" Version="2.9.2" />
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<PackageReference Include="xunit.runner.visualstudio" Version="2.8.2" />
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<PackageReference Include="coverlet.collector" Version="6.0.2" />
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</ItemGroup>
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<ItemGroup>

‎SentimentAnalyzer/README.md‎

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# SentimentAnalyzer - On-device (offline) Sentiment Analysis for .NET Standard apps
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This is a library which can be used to consume a model which I created using ML.NET.
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For further information, you can always have a look at my [blog](https://www.arafattehsin.com/blog/sentimentanalyzer-ondevice-machine-learning/)
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## Quick Start
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```c#
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# SentimentAnalyzer
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[![NuGet](https://img.shields.io/nuget/v/SentimentAnalyzer.svg)](https://www.nuget.org/packages/SentimentAnalyzer/)
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[![NuGet Downloads](https://img.shields.io/nuget/dt/SentimentAnalyzer.svg)](https://www.nuget.org/packages/SentimentAnalyzer/)
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[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
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**On-device (offline) Sentiment Analysis for .NET applications**
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A cross-platform, privacy-first library for sentiment analysis that runs entirely on-device without requiring internet connectivity. Powered by [ML.NET 5.0](https://dot.net/ml).
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## ✨ Features
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- 🔒 **Privacy-first** - All processing happens on-device, no data leaves your app
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- 📴 **Fully offline** - No internet connection required
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- 🚀 **Cross-platform** - Works on .NET Standard 2.0, .NET 8, .NET 10, MAUI, Blazor, Unity
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- ⚡ **Fast** - Thread-safe singleton pattern for optimal performance
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- 📦 **Lightweight** - Single NuGet package, no external dependencies
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## 📦 Installation
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```bash
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dotnet add package SentimentAnalyzer
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```
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Or via Package Manager:
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```powershell
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Install-Package SentimentAnalyzer
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```
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## 🚀 Quick Start
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```csharp
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using SentimentAnalyzer;
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var sentiment = Sentiments.Predict("some string");
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// Analyze sentiment
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var result = Sentiments.Predict("This product is amazing!");
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Console.WriteLine($"Sentiment: {(result.Prediction ? "Positive" : "Negative")}");
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Console.WriteLine($"Confidence: {result.Score:P2}");
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```
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`Predict` returns a `SentimentPrediction` which contains:
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## 📖 API Reference
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### `Sentiments.Predict(string text)`
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Analyzes the sentiment of the provided text.
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**Parameters:**
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- `text` - The text to analyze
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**Returns:** `SentimentPrediction`
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- `Prediction` (`bool`) - `true` for Positive sentiment, `false` for Negative sentiment
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- `Score` (`float`) - Confidence score (0.0 to 1.0)
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### Example Usage
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```csharp
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using SentimentAnalyzer;
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// Positive sentiment
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var positive = Sentiments.Predict("I love this! Best purchase ever!");
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// positive.Prediction = true, positive.Score ≈ 0.95
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// Negative sentiment
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var negative = Sentiments.Predict("Terrible experience, very disappointed.");
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// negative.Prediction = false, negative.Score ≈ 0.12
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```
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## 🎯 Platform Support
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| Platform | Supported | Target Framework |
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| --------------------- | --------- | ---------------- |
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| .NET Framework 4.6.1+ | ✅ | netstandard2.0 |
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| .NET Core 2.0+ | ✅ | netstandard2.0 |
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| .NET 5/6/7 | ✅ | netstandard2.0 |
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| .NET 8 (LTS) | ✅ | net8.0 |
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| .NET 10 (LTS) | ✅ | net10.0 |
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| .NET MAUI | ✅ | All targets |
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| Blazor Server | ✅ | All targets |
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| Blazor WebAssembly | ✅ | netstandard2.0 |
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| Unity | ✅ | netstandard2.0 |
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## 🔄 Migration from v1.x
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Version 2.0 maintains **full backward compatibility**. No code changes required:
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```xml
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<!-- Just update the version -->
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<PackageReference Include="SentimentAnalyzer" Version="2.0.0" />
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```
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## 📚 Learn More
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- [GitHub Repository](https://github.com/arafattehsin/SentimentAnalyzer)
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- [Blog Post: On-device Machine Learning](https://www.arafattehsin.com/blog/sentimentanalyzer-ondevice-machine-learning/)
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- [ML.NET Documentation](https://docs.microsoft.com/dotnet/machine-learning/)
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## 📄 License
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- `Prediction` (`bool`) - `true` is Positive sentiment, `false` is Negative sentiment.
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- `Score` (`float`) - A score representing the model's accuracy
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MIT License - see the [LICENSE](https://github.com/arafattehsin/SentimentAnalyzer/blob/main/LICENSE) file for details.

‎SentimentAnalyzer/SentimentAnalyzer.csproj‎

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<Project Sdk="Microsoft.NET.Sdk">
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<PropertyGroup>
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<TargetFramework>netstandard2.0</TargetFramework>
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<Version>1.2.3</Version>
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<TargetFrameworks>netstandard2.0;net8.0;net10.0</TargetFrameworks>
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<Version>2.0.0</Version>
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<Authors>Arafat Tehsin</Authors>
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<Description>Semantic Analyzer is an on-device (offline) open-source library to find out what customers think of your brand or topic by analyzing raw text for clues about positive or negative sentiment. This library returns a sentiment probability and score along with the prediction flags (true for Positive, false for Negative). Powered by Microsoft ML.NET</Description>
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<Copyright>Copyright © 2021</Copyright>
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<Description>SentimentAnalyzer is an on-device (offline) open-source library to find out what customers think of your brand or topic by analyzing raw text for clues about positive or negative sentiment. This library returns a sentiment probability and score along with the prediction flags (true for Positive, false for Negative). Powered by Microsoft ML.NET 5.0. Works on .NET Standard 2.0, .NET 8, .NET 10, MAUI, Blazor, and more.</Description>
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<Copyright>Copyright © 2026</Copyright>
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<PackageLicenseExpression>MIT</PackageLicenseExpression>
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<PackageProjectUrl>https://www.nuget.org/packages/SentimentAnalyzer/</PackageProjectUrl>
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<RepositoryUrl>https://github.com/arafattehsin/SentimentAnalyzer/</RepositoryUrl>
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<RepositoryType></RepositoryType>
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<PackageReleaseNotes>This release contains the performance improvements for the SentimentAnalyzer based upon the singleton pattern. It is based on ML.NET version 1.5.5</PackageReleaseNotes>
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<PackageTags>Sentiment, ML.NET, Text Analytics</PackageTags>
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<RepositoryType>git</RepositoryType>
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<PackageReleaseNotes>Major upgrade to ML.NET 5.0.0 with multi-targeting support for .NET Standard 2.0, .NET 8, and .NET 10. Cross-platform compatible with MAUI, Blazor, Unity, and more.</PackageReleaseNotes>
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<PackageTags>Sentiment;ML.NET;Text Analytics;NLP;Machine Learning;Offline;On-Device;Cross-Platform</PackageTags>
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<PackageReadmeFile>README.md</PackageReadmeFile>
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<LangVersion>latest</LangVersion>
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<Nullable>disable</Nullable>
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<ImplicitUsings>disable</ImplicitUsings>
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</PropertyGroup>
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<ItemGroup>
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<None Include="..\README.md" Pack="true" PackagePath="\" />
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</ItemGroup>
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<EmbeddedResource Include="MLModels\SentimentModel.zip" />
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</ItemGroup>
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<PackageReference Include="Microsoft.ML" Version="1.5.5" />
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<PackageReference Include="Microsoft.ML" Version="5.0.0" />
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</ItemGroup>
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</Project>

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