12RanText & sentiment

Stress in social media posts

I cleaned 2,838 posts, built a bag-of-words matrix with 7,842 terms, trained a Bernoulli naive Bayes classifier and tried it on two sentences I typed.

Original tutorial by Aman Kharwal: Stress Detection (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 #
Posts vectorised	2,838	13
Vocabulary size	7,842	13

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

No accuracy was ever printed, so there is nothing to judge the model by.

The data

Labelled Reddit posts from mental-health and relationship communities, re-uploaded from the Dreaddit research dataset.

The posts describe people's mental health. None of the text is shown on this site.

What I'd do differently

Report accuracy, recall for the stress class and the majority-class baseline.
Be clear that a word-count model like this should never be used to label real people.
Use the dataset from its original source and follow its terms.