| Resumen |
For predicting the success of an anime in its early stages of development, a baseline is proposed in this paper, based on the synopsis of its plot. AniSyn7 is presented, which is a corpus consisting of 6, 928 anime synopsis with binary labels of successful/unsuccesful. The corpus was explored by vectorizing the synopsis using n-grams and dependence trees, so three traditional machine learning classifiers (Support Vector Machine, Gaussian Naive Bayes, and Logistic Regression) can be employed in order to study correlation between synopsis and success.
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