Summary of A Deep Convolutional Neural Network-based Model For Aspect and Polarity Classification in Hausa Movie Reviews, by Umar Ibrahim et al.
A Deep Convolutional Neural Network-based Model for Aspect and Polarity Classification in Hausa Movie Reviews
by Umar Ibrahim, Abubakar Yakubu Zandam, Fatima Muhammad Adam, Aminu Musa
First submitted to arxiv on: 29 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Aspect-based Sentiment Analysis (ABSA) is crucial for understanding sentiment nuances in text across diverse languages and cultures. This paper introduces a novel Deep Convolutional Neural Network (CNN)-based model tailored for aspect and polarity classification in Hausa movie reviews, an underrepresented language in sentiment analysis research. The proposed model combines CNNs with attention mechanisms for aspect-word prediction, leveraging contextual information and sentiment polarities. With 91% accuracy on aspect term extraction and 92% on sentiment polarity classification, the model outperforms traditional machine models, offering insights into specific aspects and sentiments. This study advances ABSA research, particularly in underrepresented languages, with implications for cross-cultural linguistic research. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about a new way to understand how people feel about movies from different cultures. They created a special computer model that can look at movie reviews in a language called Hausa and figure out what people liked or disliked about specific parts of the movie. This is important because there aren’t many ways for computers to understand these types of languages right now. The new model is really good, it’s accurate 91% of the time when it comes to understanding what people like or dislike about a part of the movie. It also does well at figuring out how people feel overall about the movie. |
Keywords
» Artificial intelligence » Attention » Classification » Cnn » Neural network
