mlsanityData to 7 Oct 2026

Is Stance Detection Topic-Independent and Cross-topic Generalizable? -- A Reproduction Study

arXiv 2110.07693 ↗First posted 14 Oct 2021cs.CLcited by 9

Not on the map. Why?

Abstract (arXiv)

Cross-topic stance detection is the task to automatically detect stances (pro, against, or neutral) on unseen topics. We successfully reproduce state-of-the-art cross-topic stance detection work (Reimers et. al., 2019), and systematically analyze its reproducibility. Our attention then turns to the cross-topic aspect of this work, and the specificity of topics in terms of vocabulary and socio-cultural context. We ask: To what extent is stance detection topic-independent and generalizable across topics? We compare the model's performance on various unseen topics, and find topic (e.g. abortion, cloning), class (e.g. pro, con), and their interaction affecting the model's performance. We conclude that investigating performance on different topics, and addressing topic-specific vocabulary and context, is a future avenue for cross-topic stance detection.

Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 14 of its 33 references that are in the map. First posted on arXiv 14 Oct 2021.

Builds on

14 of 33 references.

References · 14

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Stance Detection on Social Media: State of the Art and Trendscited by 93
  3. 2021A Survey on Stance Detection for Mis- and Disinformation Identificationcited by 75
  4. 2018Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networkscited by 58
  5. 2019Classification and Clustering of Arguments with Contextualized Word Embeddingscited by 57
  6. 2018A Retrospective Analysis of the Fake News Challenge Stance Detection Taskcited by 49
  7. 2019Unsupervised User Stance Detection on Twittercited by 45
  8. 2020Targeting the Benchmark: On Methodology in Current Natural Language Processing Researchcited by 44
  9. 2021Adversarial Learning for Zero-Shot Stance Detection on Social Mediacited by 36
  10. 2021A Systematic Review of Reproducibility Research in Natural Language Processingcited by 34
  11. 2020Stance Detection Benchmark: How Robust Is Your Stance Detection?cited by 33
  12. 2017A simple but tough-to-beat baseline for the Fake News Challenge stance detection taskcited by 26
2 more
  1. 2020Assessing Viewpoint Diversity in Search Results Using Ranking Fairness Metricscited by 11
  2. 2020Same Side Stance Classification Task: Facilitating Argument Stance Classification by Fine-tuning a BERT Modelcited by 2

Built on by

Cited by year

Citing papers per year: 2022: 4; 2023: 2; 2024: 3.

9 papers.

  1. 2022Will It Blend? Mixing Training Paradigms & Prompting for Argument Quality Predictioncited by 7
  2. 2022Contextual information integration for stance detection via cross-attentioncited by 6
  3. 2024Dive into the Chasm: Probing the Gap between In- and Cross-Topic Generalizationcited by 6
  4. 2022The COVMis-Stance dataset: Stance Detection on Twitter for COVID-19 Misinformationcited by 4
  5. 2023Topic Ontologies for Argumentscited by 3
  6. 2023Explaining Search Result Stances to Opinionated Peoplecited by 1
  7. 2024Investigating the Robustness of Modelling Decisions for Few-Shot Cross-Topic Stance Detection: A Preregistered Studycited by 1
  8. 2024Zero-shot Cross-lingual Stance Detection via Adversarial Language Adaptationcited by 1
  9. 2022Perturbations and Subpopulations for Testing Robustness in Token-Based Argument Unit Recognitioncited by 0