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๐ข Seriously, We can't go with Big5 or other non structured descriptions to diverse large amount of characters ๐จโ๐ฉโ๐ฆโ๐ฆ from many books ๐. Instead, The factorization + open-psychometrics antonyms extracted from dialogues is a key ๐ for automatic character profiling that purely relies on book content ๐. With that, happy to share delighted to share with you ๐ more on this topic in YouTube video:
https://youtu.be/UQQsXfZyjjc
๐ From which you will find out:
โ How to perform book processing ๐ aimed at personalities extraction
โ How to impute personalities ๐จโ๐ฉโ๐ฆโ๐ฆ and character network for deep learning ๐ค
โ How to evaluate ๐ advances / experiment findings ๐งช
Additional materials:
๐ Github: https://github.com/nicolay-r/book-persona-retriever
๐ Paper: https://www.dropbox.com/scl/fi/0c2axh97hadolwphgu7it/rusnachenko2024personality.pdf?rlkey=g2yyzv01th2rjt4o1oky0q8zc&st=omssztha&dl=1
๐ Google-colab experiments: https://colab.research.google.com/github/nicolay-r/deep-book-processing/blob/master/parlai_gutenberg_experiments.ipynb
๐ฆ Task: https://github.com/nicolay-r/parlai_bookchar_task/tree/master
https://youtu.be/UQQsXfZyjjc
๐ From which you will find out:
โ How to perform book processing ๐ aimed at personalities extraction
โ How to impute personalities ๐จโ๐ฉโ๐ฆโ๐ฆ and character network for deep learning ๐ค
โ How to evaluate ๐ advances / experiment findings ๐งช
Additional materials:
๐ Github: https://github.com/nicolay-r/book-persona-retriever
๐ Paper: https://www.dropbox.com/scl/fi/0c2axh97hadolwphgu7it/rusnachenko2024personality.pdf?rlkey=g2yyzv01th2rjt4o1oky0q8zc&st=omssztha&dl=1
๐ Google-colab experiments: https://colab.research.google.com/github/nicolay-r/deep-book-processing/blob/master/parlai_gutenberg_experiments.ipynb
๐ฆ Task: https://github.com/nicolay-r/parlai_bookchar_task/tree/master
