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metalcorebear / NRCLex

An affect generator based on TextBlob and the NRC affect lexicon. Note that lexicon license is for research purposes only.
MIT License
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Capitalization Affecting Outcome #11

Open Yangyi-Zhang opened 2 years ago

Yangyi-Zhang commented 2 years ago

Hi,

Thank you for the project. I saw different outputs when alternating the capitalization of input, for example:

text = "I love to visit historical places" emotion = NRCLex(text) print(emotion.top_emotions)

yields [('positive', 0.6666666666666666)], with raw emotion score {'joy': 1, 'positive': 2}.

while if I change text to "I Love to visit historical places", the top_emotions becomes [('positive', 1.0)].

How do we explain this? I understand this might not be an issue, but I am curious as a beginner in NLP.

metalcorebear commented 2 years ago

Thanks for bringing this up. I think we need to add a line of code to make all words within the examined corpus lowercase. That should overcome this issue, since the affect word list is all lowercase.