19RanText & sentiment

Labelling reviews with VADER

I scored 20,491 hotel reviews with VADER and labelled them positive, negative or neutral from the compound score with cut-offs at plus and minus 0.05, then saved the labelled table.

Original tutorial by Aman Kharwal: Adding Labels to a Dataset for Sentiment Analysis (opens in a new tab)

What it printed in 2022

Numbers read from the saved notebook outputs. Cell numbers count every cell in the notebook, Markdown included, starting at 1.
Output	Value	Cell #
Reviews labelled positive	18,831	13
Reviews labelled negative	1,569	13
Reviews labelled neutral	91	13

Cell # counts every cell from the top of the notebook, Markdown included, starting at 1.

The data

Hotel reviews from the tutorial author's data repository. The labelled file is in the repository and is not served here.

What I'd do differently

Treat VADER labels as weak labels. Check a random sample by hand before training anything on them.
The neutral band is so narrow that only 91 reviews landed in it. Widen it or drop the class.