Skip to content
#

wordembedding

Here are 55 public repositories matching this topic...

The project researches sentiment analysis on Twitter, with the goal of evaluating the positivity, negativity or neutrality of comments. Using Word Embeddings, an advanced method in natural language processing, our model achieved a high accuracy of 96.61%. The model was trained on Twitter data and tested on a data comment dataset from Binance.

  • Updated Mar 27, 2024
  • Jupyter Notebook

Improve this page

Add a description, image, and links to the wordembedding topic page so that developers can more easily learn about it.

Curate this topic

Add this topic to your repo

To associate your repository with the wordembedding topic, visit your repo's landing page and select "manage topics."

Learn more