# Joint Aspect and Polarity Classification for Aspect-based Sentiment Analysis with End-to-End Neural Networks

arXiv: https://arxiv.org/abs/1808.09238 · HTML: https://mlsanity.com/paper/1808.09238/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 28 Aug 2018.

## Built on by (most cited first, 19 of 19)

- [A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges](https://mlsanity.com/paper/2203.01054/) (2022)
- [Solving Aspect Category Sentiment Analysis as a Text Generation Task](https://mlsanity.com/paper/2110.07310/) (2021)
- [A Survey on Aspect-Based Sentiment Classification](https://mlsanity.com/paper/2203.14266/) (2022)
- [Exploring Conditional Text Generation for Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2110.02334/) (2021)
- [BvSP: Broad-view Soft Prompting for Few-Shot Aspect Sentiment Quad Prediction](https://mlsanity.com/paper/2406.07365/) (2024)
- [Survey of Aspect-based Sentiment Analysis Datasets](https://mlsanity.com/paper/2204.05232/) (2022)
- [A Comprehensive Review on Sentiment Analysis: Tasks, Approaches and Applications](https://mlsanity.com/paper/2311.11250/) (2023)
- [Re-Evaluating GermEval17 Using German Pre-Trained Language Models](https://mlsanity.com/paper/2102.12330/) (2021)
- [Applications and Challenges of Sentiment Analysis in Real-life Scenarios](https://mlsanity.com/paper/2301.09912/) (2023)
- [Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble Approaches](https://mlsanity.com/paper/2311.05051/) (2023)
- [Large Language Models for Czech Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2508.07860/) (2025)
- [Few-shot Cross-lingual Aspect-Based Sentiment Analysis with Sequence-to-Sequence Models](https://mlsanity.com/paper/2508.07866/) (2025)
- [Improving Generative Cross-lingual Aspect-Based Sentiment Analysis with Constrained Decoding](https://mlsanity.com/paper/2508.10369/) (2025)
- [SASICM A Multi-Task Benchmark For Subtext Recognition](https://mlsanity.com/paper/2106.06944/) (2021)
- [From Stars to Insights: Exploration and Implementation of Unified Sentiment Analysis with Distant Supervision](https://mlsanity.com/paper/2305.01710/) (2023)
- [Understanding Emotion Valence is a Joint Deep Learning Task](https://mlsanity.com/paper/2305.17422/) (2023)
- [A Global Context Mechanism for Sequence Labeling](https://mlsanity.com/paper/2305.19928/) (2023)
- [Semantic-preserved Augmentation with Confidence-weighted Fine-tuning for Aspect Category Sentiment Analysis](https://mlsanity.com/paper/2506.07148/) (2025)
- [Emotion-Enhanced Multi-Task Learning with LLMs for Aspect Category Sentiment Analysis](https://mlsanity.com/paper/2511.19122/) (2025)

## Abstract (arXiv)

In this work, we propose a new model for aspect-based sentiment analysis. In contrast to previous approaches, we jointly model the detection of aspects and the classification of their polarity in an end-to-end trainable neural network. We conduct experiments with different neural architectures and word representations on the recent GermEval 2017 dataset. We were able to show considerable performance gains by using the joint modeling approach in all settings compared to pipeline approaches. The combination of a convolutional neural network and fasttext embeddings outperformed the best submission of the shared task in 2017, establishing a new state of the art.