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Wireless Networks
Erschienen in: Wireless Networks 7/2023

01.07.2023

An intelligent box office predictor based on aspect-level sentiment analysis of movie review

verfasst von: Gelan Yang, Yiyi Xu, Li Tu

Erschienen in: Wireless Networks | Ausgabe 7/2023

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Abstract

Box office is a challenging and crucial task for the movie distributors in decision making. In recent years, movie reviews are widely posted and shared on intelligent multimedia systems and everywhere. In this work, we employ both the metadata of the movie and the sentiment information of the users’ reviews to establish an intelligent predicting model. In the sentiment polarity classification model, a co-attention network-based aspect-level sentiment analysis strategy is developed by using the specific word embedding representations from both the contexts and the aspect. Considering the movie success prediction, a Softmax Discriminant Classifier is used due to its capable of dealing with non-linear issues. The sentiments from review texts, together with the movie information are taken as input variables of the predictor. Experimental outcomes verify the working performance of the proposed method which indicates that our model can be further applied to the sentiment analysis and the predicting of movie success.
Vorheriger Artikel A target behavior pattern mining and abnormal behavior monitoring based on multidimensional similarity metric
Nächster Artikel Flight data outlier detection by constrained LSTM-autoencoder

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Metadaten
Titel
An intelligent box office predictor based on aspect-level sentiment analysis of movie review
verfasst von
Gelan Yang
Yiyi Xu
Li Tu
Publikationsdatum
01.07.2023
Verlag
Springer US
Erschienen in
Wireless Networks / Ausgabe 7/2023
Print ISSN: 1022-0038
Elektronische ISSN: 1572-8196
DOI
https://doi.org/10.1007/s11276-023-03378-6

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