A python package for flexible and transparent sentiment analysis.
Project description
Asent: Fast, flexible and transparent sentiment analysis
Inspired by Vader, made using SpaCy, transparent from the start.
Installation
Installing Asent is simple using pip:
pip install asent
There is no reason to update from GitHub as the version on pypi should always be the same of on GitHub.
Simple Example
The following shows a simple example of how you can quickly apply sentiment analysis using asent. For more on using asent see the usage guides.
import spacy
import asent
# load spacy pipeline
nlp = spacy.load("en_core_web_lg")
# add the rule-based sentiment model
nlp.add_pipe("asent_en_v1")
# try an example
text = "I am not very happy, but I am also not especially sad"
doc = nlp(text)
# visualize model prediction
asent.visualize(doc, style="prediction")
If we want to know even more
# visualize the analysis performed by the model:
asent.visualize(doc[:5], style="analysis")
📖 Documentation
| Documentation | |
|---|---|
| 🔧 Installation | Installation instructions for Asent |
| 📚 Usage Guides | Guides and instructions on how to use asent and its features. |
| 📰 News and changelog | New additions, changes and version history. |
| 🎛 Documentation | The detailed reference for Asents's API. Including function documentation |
💬 Where to ask questions
| Type | |
|---|---|
| 🚨 FAQ | FAQ |
| 🚨 Bug Reports | GitHub Issue Tracker |
| 🎁 Feature Requests & Ideas | GitHub Issue Tracker |
| 👩💻 Usage Questions | GitHub Discussions |
| 🗯 General Discussion | GitHub Discussions |
🎓 Citing this work
If you use this library in your research, please cite it using:
@inproceedings{asent2021,
title={Asent: Fast, flexible and transparent sentiment analysis},
author={Kenneth Enevoldsen},
year={2021}
}
Release history Release notifications | RSS feed
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