This repository is a curated list of resources for sentiment analysis, targeting researchers, engineers, and practitioners in Natural Language Processing (NLP). It provides a comprehensive overview of frameworks, libraries, datasets, lexicons, and academic papers, aiming to be a central hub for anyone working in or exploring sentiment analysis.

How It Works

The list is organized by category, covering various programming languages (Python, Java, R, C#, Node.js), specific techniques like Aspect-Based Sentiment Analysis, and essential resources such as lexicons (AFINN, SentiWordNet, NRC-Canada) and datasets (Stanford Sentiment Treebank, Amazon Product Dataset, IMDB). It also includes links to relevant academic papers, workshops, tutorials, and APIs, offering a broad spectrum of tools and knowledge.

Quick Start & Requirements

This is a curated list, not a runnable project. To use the listed tools, users will need to install and configure them individually based on their specific requirements. Links to official documentation and demos are provided for many entries.

Highlighted Details

• Extensive coverage of sentiment analysis libraries across multiple programming languages.
• Detailed lists of sentiment lexicons and benchmark datasets for training and evaluation.
• Inclusion of academic papers and tutorials on various sentiment analysis methodologies, including deep learning and lexicon-based approaches.
• Links to relevant APIs from major cloud providers (IBM Watson, Google Cloud, Microsoft Azure) and specialized services.

Maintenance & Community

The list is maintained by laugustyniak and welcomes contributions via pull requests or direct contact. Specific community links (Discord/Slack) or roadmaps are not provided in the README.

Licensing & Compatibility

The repository itself is a list and does not have a specific license. The licenses of the individual tools and resources mentioned vary and must be checked separately. Compatibility for commercial use or closed-source linking depends entirely on the licenses of the included libraries and datasets.

Limitations & Caveats

As a curated list, this repository does not offer a unified installation or execution environment. Users must independently assess and integrate the various tools and resources, which may have differing dependencies, compatibility issues, and maintenance statuses.