# Polarity and Subjectivity Detection with Multitask Learning and BERT Embedding

arXiv: https://arxiv.org/abs/2201.05363 · HTML: https://mlsanity.com/paper/2201.05363/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 39 references that are in the map.
- First posted on arXiv 14 Jan 2022.

## Builds on (most cited first, 14 of 14)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Cross-stitch Networks for Multi-task Learning](https://mlsanity.com/paper/1604.03539/) (2016)
- [Multi-Task Learning with Deep Neural Networks: A Survey](https://mlsanity.com/paper/2009.09796/) (2020)
- [Recurrent Neural Network for Text Classification with Multi-Task Learning](https://mlsanity.com/paper/1605.05101/) (2016)
- [Adversarial Multi-task Learning for Text Classification](https://mlsanity.com/paper/1704.05742/) (2017)
- [All-in-one: Multi-task Learning for Rumour Verification](https://mlsanity.com/paper/1806.03713/) (2018)
- [Ask the GRU: Multi-Task Learning for Deep Text Recommendations](https://mlsanity.com/paper/1609.02116/) (2016)
- [When is multitask learning effective? Semantic sequence prediction under varying data conditions](https://mlsanity.com/paper/1612.02251/) (2016)
- [Sentiment and Sarcasm Classification with Multitask Learning](https://mlsanity.com/paper/1901.08014/) (2019)
- [Self-Adaptive Hierarchical Sentence Model](https://mlsanity.com/paper/1504.05070/) (2015)
- [Multitask Learning for Fine-Grained Twitter Sentiment Analysis](https://mlsanity.com/paper/1707.03569/) (2017)
- [Translations as Additional Contexts for Sentence Classification](https://mlsanity.com/paper/1806.05516/) (2018)

## Built on by (most cited first, 3 of 3)

- [A Survey on Semantic Processing Techniques](https://mlsanity.com/paper/2310.18345/) (2023)
- [Gpachov at CheckThat! 2023: A Diverse Multi-Approach Ensemble for Subjectivity Detection in News Articles](https://mlsanity.com/paper/2309.06844/) (2023)
- [Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation](https://mlsanity.com/paper/2508.19966/) (2025)

## Abstract (arXiv)

Multitask learning often helps improve the performance of related tasks as these often have inter-dependence on each other and perform better when solved in a joint framework. In this paper, we present a deep multitask learning framework that jointly performs polarity and subjective detection. We propose an attention-based multitask model for predicting polarity and subjectivity. The input sentences are transformed into vectors using pre-trained BERT and Glove embeddings, and the results depict that BERT embedding based model works better than the Glove based model. We compare our approach with state-of-the-art models in both subjective and polarity classification single-task and multitask frameworks. The proposed approach reports baseline performances for both polarity detection and subjectivity detection.