Classifying movie genres by analyzing text reviews
Computation and Language
2018-02-16 v1
Abstract
This paper proposes a method for classifying movie genres by only looking at text reviews. The data used are from Large Movie Review Dataset v1.0 and IMDb. This paper compared a K-nearest neighbors (KNN) model and a multilayer perceptron (MLP) that uses tf-idf as input features. The paper also discusses different evaluation metrics used when doing multi-label classification. For the data used in this research, the KNN model performed the best with an accuracy of 55.4\% and a Hamming loss of 0.047.
Keywords
Cite
@article{arxiv.1802.05322,
title = {Classifying movie genres by analyzing text reviews},
author = {Adam Nyberg},
journal= {arXiv preprint arXiv:1802.05322},
year = {2018}
}