SuperStyl
scattertext
| SuperStyl | scattertext | |
|---|---|---|
| 2 | 3 | |
| 20 | 2,203 | |
| - | - | |
| 9.0 | 4.7 | |
| 7 days ago | 2 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | Apache License 2.0 |
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.
SuperStyl
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[N] Who Is Behind QAnon? Linguistic Detectives Find Fingerprints using statistics and machine learning
One of the repos linked by OP mention this Python package in the README.
The French team has put their Python code on GitHub, so from a first glance, after tokenization, features extraction based on words and letters frequency then classification using SVM. The problem is to grab the data yourself...
scattertext
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Clustering of text - Where to start?
If what you want is to determine how similar two categories are, or to learn something about the structure or words that compose those categories, you might consider word shift graphs or Scattertext.
- [Data] Principali parole degli ultimi (circa) 200 post sul sub
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Alternate approaches to TF-IDF?
Other suggestions: Take a look at Scattertext. Compare keywords to the problem of aspect extraction. I think an underutilized way to look at textual data when you have a single group of interest is the word-frequency-based odds ratio.
What are some alternatives?
100-Days-Of-ML-Code - 100 Days of ML Coding
BERTopic - Leveraging BERT and c-TF-IDF to create easily interpretable topics.
JGAAP - The Java Graphical Authorship Attribution Program
KeyBERT - Minimal keyword extraction with BERT
Machine-Learning-Cyrillic-Classifier - This is a web app where you can draw a letter in the russian alphabet and the ML algorithm will predict the letter that you drew.
stopwords-it - Italian stopwords collection
svm-pytorch - Linear SVM with PyTorch
word_cloud - A little word cloud generator in Python
dzetsaka - dzetsaka : classification plugin for Qgis
shifterator - Interpretable data visualizations for understanding how texts differ at the word level
lit - The Learning Interpretability Tool: Interactively analyze ML models to understand their behavior in an extensible and framework agnostic interface.
yake - Single-document unsupervised keyword extraction