Sentiment
awesome-sentiment-analysis
Sentiment | awesome-sentiment-analysis | |
---|---|---|
- | 1 | |
100 | 526 | |
0.0% | - | |
1.7 | 1.9 | |
about 1 year ago | 6 months ago | |
PHP | ||
MIT License | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Sentiment
We haven't tracked posts mentioning Sentiment yet.
Tracking mentions began in Dec 2020.
awesome-sentiment-analysis
-
What are the ways to handle out of domain inputs for text classification?
Get or generate negative class data. There are adversarial approaches that can improve domain generalization, but it's best to acquire more data from diverse sources. You mentioned you're working on sentiment in one of your comments- there are a ton of open-source sentiment datasets, at least for English, comprising millions of rows of data. Randomly sample from a wide variety of them to hit as many domains as possible. It's also worth including a neutral class.
What are some alternatives?
RubixML - A high-level machine learning and deep learning library for the PHP language.
awesome-hungarian-nlp - A curated list of NLP resources for Hungarian
Iris - The original lightweight introduction to machine learning in Rubix ML using the famous Iris dataset and the K Nearest Neighbors classifier.
obsei - Obsei is a low code AI powered automation tool. It can be used in various business flows like social listening, AI based alerting, brand image analysis, comparative study and more .
spaCy - 💫 Industrial-strength Natural Language Processing (NLP) in Python
afinn - AFINN sentiment analysis in Python
backprop - Heterogeneous automatic differentiation ("backpropagation") in Haskell
nlphose - Enables creation of complex NLP pipelines in seconds, for processing static files or streaming text, using a set of simple command line tools. Perform multiple operation on text like NER, Sentiment Analysis, Chunking, Language Identification, Q&A, 0-shot Classification and more by executing a single command in the terminal. Can be used as a low code or no code Natural Language Processing solution. Also works with Kubernetes and PySpark !
pytorch-sentiment-analysis - Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
Blind-App-Reviews - Scraped reviews of over 25 companies from the Blind App ⚡️
financial-news-dataset - Reuters and Bloomberg
lemmatization-lists - Machine-readable lists of lemma-token pairs in 23 languages.