# Effective LSTMs for Target-Dependent Sentiment Classification

arXiv: https://arxiv.org/abs/1512.01100 · HTML: https://mlsanity.com/paper/1512.01100/

## Key facts

- Cited by 82 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Dec 2015.

## Built on by (most cited first, 30 of 82)

- [A Unified Generative Framework for Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2106.04300/) (2021)
- [RLHF from Heterogeneous Feedback via Personalization and Preference Aggregation](https://mlsanity.com/paper/2405.00254/) (2024)
- [DialogueCRN: Contextual Reasoning Networks for Emotion Recognition in Conversations](https://mlsanity.com/paper/2106.01978/) (2021)
- [A Joint Training Dual-MRC Framework for Aspect Based Sentiment Analysis](https://mlsanity.com/paper/2101.00816/) (2021)
- [A Survey on Aspect-Based Sentiment Analysis: Tasks, Methods, and Challenges](https://mlsanity.com/paper/2203.01054/) (2022)
- [LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model](https://mlsanity.com/paper/2304.06248/) (2023)
- [Does syntax matter? A strong baseline for Aspect-based Sentiment Analysis with RoBERTa](https://mlsanity.com/paper/2104.04986/) (2021)
- [A Systematic Review of Reproducibility Research in Natural Language Processing](https://mlsanity.com/paper/2103.07929/) (2021)
- [Character-level White-Box Adversarial Attacks against Transformers via Attachable Subwords Substitution](https://mlsanity.com/paper/2210.17004/) (2022)
- [DiaASQ : A Benchmark of Conversational Aspect-based Sentiment Quadruple Analysis](https://mlsanity.com/paper/2211.05705/) (2022)
- [SentiPrompt: Sentiment Knowledge Enhanced Prompt-Tuning for Aspect-Based Sentiment Analysis](https://mlsanity.com/paper/2109.08306/) (2021)
- [On the Robustness of Aspect-based Sentiment Analysis: Rethinking Model, Data, and Training](https://mlsanity.com/paper/2304.09563/) (2023)
- [A Survey on Aspect-Based Sentiment Classification](https://mlsanity.com/paper/2203.14266/) (2022)
- [Knowledge Graph Augmented Network Towards Multiview Representation Learning for Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2201.04831/) (2022)
- [Large Language Models Meet Text-Centric Multimodal Sentiment Analysis: A Survey](https://mlsanity.com/paper/2406.08068/) (2024)
- [Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification](https://mlsanity.com/paper/2103.11794/) (2021)
- [METS-CoV: A Dataset of Medical Entity and Targeted Sentiment on COVID-19 Related Tweets](https://mlsanity.com/paper/2209.13773/) (2022)
- [Understand me, if you refer to Aspect Knowledge: Knowledge-aware Gated Recurrent Memory Network](https://mlsanity.com/paper/2108.02352/) (2021)
- [Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2110.13398/) (2021)
- [Incorporating Dynamic Semantics into Pre-Trained Language Model for Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2203.16369/) (2022)
- [Exploiting Position Bias for Robust Aspect Sentiment Classification](https://mlsanity.com/paper/2105.14210/) (2021)
- [UnifiedABSA: A Unified ABSA Framework Based on Multi-task Instruction Tuning](https://mlsanity.com/paper/2211.10986/) (2022)
- [Out of Context: A New Clue for Context Modeling of Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2106.10816/) (2021)
- [DigNet: Digging Clues from Local-Global Interactive Graph for Aspect-level Sentiment Classification](https://mlsanity.com/paper/2201.00989/) (2022)
- [Reproducibility, Replicability and Beyond: Assessing Production Readiness of Aspect Based Sentiment Analysis in the Wild](https://mlsanity.com/paper/2101.09449/) (2021)
- [A Dataset and BERT-based Models for Targeted Sentiment Analysis on Turkish Texts](https://mlsanity.com/paper/2205.04185/) (2022)
- [Aspect-Based Sentiment Analysis with Explicit Sentiment Augmentations](https://mlsanity.com/paper/2312.10961/) (2023)
- [A More Fine-Grained Aspect-Sentiment-Opinion Triplet Extraction Task](https://mlsanity.com/paper/2103.15255/) (2021)
- [Iterative Data Generation with Large Language Models for Aspect-based Sentiment Analysis](https://mlsanity.com/paper/2407.00341/) (2024)
- [Enhanced Aspect-Based Sentiment Analysis Models with Progressive Self-supervised Attention Learning](https://mlsanity.com/paper/2103.03446/) (2021)

## Abstract (arXiv)

Target-dependent sentiment classification remains a challenge: modeling the semantic relatedness of a target with its context words in a sentence. Different context words have different influences on determining the sentiment polarity of a sentence towards the target. Therefore, it is desirable to integrate the connections between target word and context words when building a learning system. In this paper, we develop two target dependent long short-term memory (LSTM) models, where target information is automatically taken into account. We evaluate our methods on a benchmark dataset from Twitter. Empirical results show that modeling sentence representation with standard LSTM does not perform well. Incorporating target information into LSTM can significantly boost the classification accuracy. The target-dependent LSTM models achieve state-of-the-art performances without using syntactic parser or external sentiment lexicons.