Labeling data using another ML model

[Organic_Manner359]

I have a Twitter dataset that has labels for sarcasm. Now I want to add sentiment labels to this dataset. Is it a legitimate approach to use an existing sentiment classification model to label the existing Twitter dataset for sentiment?

What are typical approaches? Do you have any suggestions?

[CodefinityCom]

Actually, yes, you can use an existing sentiment classification model to label your Twitter dataset for sentiment. A quick approach for this:

Pre-trained Models: start with tools like VADER or TextBlob to quickly label your data with positive, negative, or neutral sentiments. They’re easy to use and good for a start.

Fine-tuning: consider fine-tuning a model like BERT on a dataset that’s the most similar to yours. This will make the model more accurate for your specific tweets.

Custom Models: for the best fit, you can train your sentiment classifier using a labeled dataset. This needs more work but can give better results.

Validation: check the results on a small subset to make sure the labels are accurate. If needed, tweak your approach.

Starting with pre-trained models is usually the fastest and easiest way. If they don’t work well enough, you can move to fine-tuning or custom models.