# Toward Extractive Summarization of Online Forum Discussions via Hierarchical Attention Networks

arXiv: https://arxiv.org/abs/1805.10390 · HTML: https://mlsanity.com/paper/1805.10390/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 May 2018.

## Built on by (most cited first, 8 of 8)

- [Enhance Incomplete Utterance Restoration by Joint Learning Token Extraction and Text Generation](https://mlsanity.com/paper/2204.03958/) (2022)
- [Understanding and Supporting Formal Email Exchange by Answering AI-Generated Questions](https://mlsanity.com/paper/2502.03804/) (2025)
- [Taxonomy of Abstractive Dialogue Summarization: Scenarios, Approaches and Future Directions](https://mlsanity.com/paper/2210.09894/) (2022)
- [Improving Online Forums Summarization via Hierarchical Unified Deep Neural Network](https://mlsanity.com/paper/2103.13587/) (2021)
- [TANet: Thread-Aware Pretraining for Abstractive Conversational Summarization](https://mlsanity.com/paper/2204.04504/) (2022)
- [Using attention methods to predict judicial outcomes](https://mlsanity.com/paper/2207.08823/) (2022)
- [Meeting Decision Tracker: Making Meeting Minutes with De-Contextualized Utterances](https://mlsanity.com/paper/2210.11374/) (2022)
- [Indicative Summarization of Long Discussions](https://mlsanity.com/paper/2311.01882/) (2023)

## Abstract (arXiv)

Forum threads are lengthy and rich in content. Concise thread summaries will benefit both newcomers seeking information and those who participate in the discussion. Few studies, however, have examined the task of forum thread summarization. In this work we make the first attempt to adapt the hierarchical attention networks for thread summarization. The model draws on the recent development of neural attention mechanisms to build sentence and thread representations and use them for summarization. Our results indicate that the proposed approach can outperform a range of competitive baselines. Further, a redundancy removal step is crucial for achieving outstanding results.