Comments (2)
bfelbo
commented on May 20, 2024
The way we do it is to make a prediction without each word in the sentence. The words that when excluded make the prediction differ the most has the highest emotional impact. It shouldn't be too hard for you to implement using the standard DeepMoji model in this repo :)
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Megh-Thakkar
commented on May 20, 2024
That is really smart. Thank you.
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Related Issues (20)
- Live Demo is down HOT 3
- How did you relate data labels to emojis HOT 1
- Returning "confidence" for each predicted emoji?
- [Errno 2] No such file or directory: 'model/deepmoji_weights.hdf5' HOT 4
- Fine-tuning to predict emotion labels HOT 8
- How to start training deepmoji on a new language corpus? HOT 2
- Building similar model for Hindi(India) language. HOT 1
- Is training dataset available? HOT 1
- How are emojis handled? How are they encoded? HOT 1
- Deploy model in mobile. HOT 2
- How is emotional impact of words highlighted? HOT 5
- Is the training data private? HOT 1
- index error with SCv1 and SCv2-GEN
- Benchmark Dataset Splits
- Deepmoji Live demo is down HOT 2
- cannot connect to remote server HOT 1
- cannot connect to remote server HOT 1
- how to return impact associated to each word per sentence HOT 17
- confusion in finetuning script
- the link https://deepmoji.mit.edu/ is broken HOT 3
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