Data Science Asked by a125 on December 11, 2020
After performing some sentiment analysis, I have a dataset that looks like this:
For different products, using online reviews, I have obtained some values for positive/negative sentiments. However, now I am unable to figure out how to draw conclusions for this.
I had the idea of using correlation but need ideas on what features could be created & what comparisons could be made?
The dataset includes different "Features" like webcam, screen, mousepad for different products (product name).
id Date Website Product Name Brand Stars Feature Sentiment Positive Negative Anger Happiness Annoyance
0 2020.8.03 eBay Lenovo Hi-Fi 320 Lenovo 4 Screen NEGATIVE 0.000047 0.999851 0.000101 0.108132 0.248220
Depends what your Goal is.
But generally you see that positive and negative Sentiment probabilities are disjunct. Meaning your model focuses for one class only, negative one. ANd thats it, you conclude your data sample belongs to class "Negative". What that means, depends on the Definition of this class.
Answered by Noah Weber on December 11, 2020
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