mlsanityData to 7 Oct 2026

Template-based Abstractive Microblog Opinion Summarisation

arXiv 2208.04083 ↗First posted 8 Aug 2022cs.CL cs.LGcited by 9

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Abstract (arXiv)

We introduce the task of microblog opinion summarisation (MOS) and share a dataset of 3100 gold-standard opinion summaries to facilitate research in this domain. The dataset contains summaries of tweets spanning a 2-year period and covers more topics than any other public Twitter summarisation dataset. Summaries are abstractive in nature and have been created by journalists skilled in summarising news articles following a template separating factual information (main story) from author opinions. Our method differs from previous work on generating gold-standard summaries from social media, which usually involves selecting representative posts and thus favours extractive summarisation models. To showcase the dataset's utility and challenges, we benchmark a range of abstractive and extractive state-of-the-art summarisation models and achieve good performance, with the former outperforming the latter. We also show that fine-tuning is necessary to improve performance and investigate the benefits of using different sample sizes.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 37 of its 74 references that are in the map. First posted on arXiv 8 Aug 2022.

Builds on

37 of 74 references.

References · 37

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25 more
  1. 2016Ups and Downs: Modeling the Visual Evolution of Fashion Trends with One-Class Collaborative Filteringcited by 517
  2. 2019Multi-News: a Large-Scale Multi-Document Summarization Dataset and Abstractive Hierarchical Modelcited by 431
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Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 2; 2024: 3; 2025: 2; 2026: 1.

9 papers.

  1. 2023Examining Bias in Opinion Summarisation Through the Perspective of Opinion Diversitycited by 14
  2. 2024Bias in Opinion Summarisation from Pre-training to Adaptation: A Case Study in Political Biascited by 12
  3. 2022Unsupervised Opinion Summarisation in the Wasserstein Spacecited by 2
  4. 2025Less Is More? Examining Fairness in Pruned Large Language Models for Summarising Opinionscited by 2
  5. 2023UniPoll: A Unified Social Media Poll Generation Framework via Multi-Objective Optimizationcited by 1
  6. 2024Generating Zero-shot Abstractive Explanations for Rumour Verificationcited by 1
  7. 2024Coverage-based Fairness in Multi-document Summarizationcited by 1
  8. 2025OPOR-Bench: Evaluating Large Language Models on Online Public Opinion Report Generationcited by 0
  9. 2026The GDN-CC Dataset: Automatic Corpus Clarification for AI-enhanced Democratic Citizen Consultationscited by 0