cbaziotis/datastories-semeval2017-task6
Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".
This project helps researchers and data scientists analyze and compare the perceived humor in short texts, like social media posts. It takes pairs of text inputs and determines if one is funnier or more humorous than the other, or if they're equally funny. This is particularly useful for those studying online humor, sentiment analysis, or social media content.
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Use this if you need to build and train a deep learning model to automatically assess and compare the humor level of short text snippets.
Not ideal if you're looking for an out-of-the-box API to classify humor without needing to train or fine-tune models.
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Language
Python
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Last pushed
Oct 16, 2017
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