mlsanityData to 14 Oct 2026

MITRE at SemEval-2016 Task 6: Transfer Learning for Stance Detection

arXiv 1606.03784 ↗First posted 13 Jun 2016cs.AI cs.CLcited by 27

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Abstract (arXiv)

We describe MITRE's submission to the SemEval-2016 Task 6, Detecting Stance in Tweets. This effort achieved the top score in Task A on supervised stance detection, producing an average F1 score of 67.8 when assessing whether a tweet author was in favor or against a topic. We employed a recurrent neural network initialized with features learned via distant supervision on two large unlabeled datasets. We trained embeddings of words and phrases with the word2vec skip-gram method, then used those features to learn sentence representations via a hashtag prediction auxiliary task. These sentence vectors were then fine-tuned for stance detection on several hundred labeled examples. The result was a high performing system that used transfer learning to maximize the value of the available training data.

Key facts. Cited by 27 papers in the map (data through 14 Oct 2026). First posted on arXiv 13 Jun 2016.

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Citing papers per year: 2021: 6; 2022: 7; 2023: 6; 2024: 3; 2025: 2; 2026: 3.

27 papers.

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  1. 2023Can Large Language Models Transform Computational Social Science?cited by 250
  2. 2022POLITICS: Pretraining with Same-story Article Comparison for Ideology Prediction and Stance Detectioncited by 51
  3. 2021Adversarial Learning for Zero-Shot Stance Detection on Social Mediacited by 37
  4. 2023Prompting and Fine-Tuning Open-Sourced Large Language Models for Stance Classificationcited by 17
  5. 2022Exploiting Sentiment and Common Sense for Zero-shot Stance Detectioncited by 16
  6. 2022Improved Target-specific Stance Detection on Social Media Platforms by Delving into Conversation Threadscited by 16
  7. 2023MGTAB: A Multi-Relational Graph-Based Twitter Account Detection Benchmarkcited by 16
  8. 2021MeLT: Message-Level Transformer with Masked Document Representations as Pre-Training for Stance Detectioncited by 11
  9. 2025Zero-Shot Conversational Stance Detection: Dataset and Approachescited by 11
  10. 2021Semi-automatic Generation of Multilingual Datasets for Stance Detection in Twittercited by 10
  11. 2024A Survey of Stance Detection on Social Media: New Directions and Perspectivescited by 8
  12. 2021Introduction to Neural Transfer Learning with Transformers for Social Science Text Analysiscited by 6
15 more
  1. 2021Adapting to the Long Tail: A Meta-Analysis of Transfer Learning Research for Language Understanding Taskscited by 6
  2. 2022Explainable Patterns for Distinction and Prediction of Moral Judgement on Redditcited by 6
  3. 2022ExaASC: A General Target-Based Stance Detection Corpus in Arabic Languagecited by 5
  4. 2024Stance Detection on Social Media with Fine-Tuned Large Language Modelscited by 5
  5. 2022Writing about COVID-19 vaccines: Emotional profiling unravels how mainstream and alternative press framed AstraZeneca, Pfizer and vaccination campaignscited by 3
  6. 2023Hashtag-Guided Low-Resource Tweet Classificationcited by 3
  7. 2021A Weakly Supervised Approach for Classifying Stance in Twitter Repliescited by 2
  8. 2023Guiding Computational Stance Detection with Expanded Stance Triangle Frameworkcited by 2
  9. 2024Zero-shot Cross-lingual Stance Detection via Adversarial Language Adaptationcited by 1
  10. 2026Zero-Shot Stance Detection in the Wild: Dynamic Target Generation and Multi-Target Adaptationcited by 1
  11. 2022Turning Stocks into Memes: A Dataset for Understanding How Social Communities Can Drive Wall Streetcited by 0
  12. 2023Multi-label and Multi-target Sampling of Machine Annotation for Computational Stance Detectioncited by 0
  13. 2025Multilingual Target-Stance Extractioncited by 0
  14. 2026StanceFlip: A Comprehensive Multi-Dimensional Benchmark for Multimodal Conversational Stance Flipping Forecastingcited by 0
  15. 2026From Two Passes to One: Compact and Efficient Target-Stance Extractioncited by 0