Fine-Tune Longformer for Jointly Predicting Rumor Stance and Veracity

Increased usage of social media caused the popularity of news and events that are not even verified, resulting in the spread of rumors all over the web. Due to widely available social media platforms and increased usage caused the data to be available in large amounts. The manual methods to process such data is costly and time-taking, so there has been increased attention to process and verify such content automatically for the presence of rumors. Lots of research studies reveal that identifying the stances of posts in the discussion thread of such events and news is an important preceding step before detecting the rumor veracity. In this paper, we propose a multi-task learning framework for jointly predicting rumor stance and veracity on the dataset released at SemEval 2019 RumorEval: Determining rumor veracity and support for rumors (SemEval 2019 Task 7), which includes social media rumors stem from a variety of breaking news stories from Reddit as well as Twitter. Our framework consists of two parts: a) The bottom part of our framework classifies the stance for each post in the conversation thread (discussing a rumor) via modeling the multi-turn conversation so that each post aware of its neighboring posts. b) The upper part predicts the rumor veracity of the conversation thread respecting the stance evolution obtained from the bottom part. Experimental results on SemEval 2019 Task 7 dataset show that our method outperforms previous methods on both rumor stance classification and veracity prediction.

• Publication year

  2020

• Venue

  COMAD/CODS

• Publication date

  2020-07-15

• Fields of study

  Computer Science

• Identifiers
  DOI 10.1145/3430984.3431007arXiv 2007.07803
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Longformer: The Long-Document Transformer

  2020cited by this paper
• Rumor Detection on Social Media: Datasets, Methods and Opportunities

  2019influential reference
• CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against Rumors

  2019cited by this paper
• BUT-FIT at SemEval-2019 Task 7: Determining the Rumour Stance with Pre-Trained Deep Bidirectional Transformers

  2019influential reference
• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

  2019cited by this paper
• Modeling Conversation Structure and Temporal Dynamics for Jointly Predicting Rumor Stance and Veracity

  2019influential reference
• RoBERTa: A Robustly Optimized BERT Pretraining Approach

  2019cited by this paper
• Pay Less Attention with Lightweight and Dynamic Convolutions

  2019cited by this paper
• Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation Structure

  2019influential reference
• Language Models are Unsupervised Multitask Learners

  2019cited by this paper
• Proceedings of the Second Workshop on Natural Language Processing for Internet Freedom: Censorship, Disinformation, and Propaganda

  2019cited by this paper
• BLCU_NLP at SemEval-2019 Task 7: An Inference Chain-based GPT Model for Rumour Evaluation

  2019influential reference
• eventAI at SemEval-2019 Task 7: Rumor Detection on Social Media by Exploiting Content, User Credibility and Propagation Information

  2019influential reference
• The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation

  2018cited by this paper
• Predicting Factuality of Reporting and Bias of News Media Sources

  2018cited by this paper
• HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

  2018cited by this paper
• SemEval-2019 Task 7: RumourEval, Determining Rumour Veracity and Support for Rumours

  2018influential reference
• Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content

  2018cited by this paper
• Identifying and Understanding User Reactions to Deceptive and Trusted Social News Sources

  2018cited by this paper
• The spread of true and false news online

  2018cited by this paper
• Automatic Stance Detection Using End-to-End Memory Networks

  2018cited by this paper
• False Information on Web and Social Media: A Survey

  2018cited by this paper
• Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

  2018cited by this paper
• Deep Contextualized Word Representations

  2018cited by this paper
• TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

  2017cited by this paper
• Where the Truth Lies: Explaining the Credibility of Emerging Claims on the Web and Social Media

  2017cited by this paper
• Turing at SemEval-2017 Task 8: Sequential Approach to Rumour Stance Classification with Branch-LSTM

  2017influential reference
• UWaterloo at SemEval-2017 Task 8: Detecting Stance towards Rumours with Topic Independent Features

  2017influential reference
• SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours

  2017cited by this paper
• Constructing Datasets for Multi-hop Reading Comprehension Across Documents

  2017cited by this paper
• Attention is All you Need

  2017influential reference
• Detect Rumors in Microblog Posts Using Propagation Structure via Kernel Learning

  2017cited by this paper
• Deception Detection and Rumor Debunking for Social Media

  2017cited by this paper
• Detection and Resolution of Rumours in Social Media

  2017cited by this paper
• SemEval-2016 Task 6: Detecting Stance in Tweets

  2016cited by this paper
• News Verification by Exploiting Conflicting Social Viewpoints in Microblogs

  2016cited by this paper
• Layer Normalization

  2016cited by this paper
• Rumor Identification and Belief Investigation on Twitter

  2016cited by this paper
• Human emotions have deep evolutionary roots, a fact that may explain their complexity and provide tools for clinical practice

  2016influential reference
• Stance Detection with Bidirectional Conditional Encoding

  2016cited by this paper
• #Unconfirmed: Classifying Rumor Stance in Crisis-Related Social Media Messages

  2016cited by this paper
• Stance Classification in Rumours as a Sequential Task Exploiting the Tree Structure of Social Media Conversations

  2016influential reference
• Rumor Detection and Classification for Twitter Data

  2015cited by this paper
• Automatic Detection of Rumor on Social Network

  2015influential reference
• Real-time Rumor Debunking on Twitter

  2015cited by this paper
• Analysing How People Orient to and Spread Rumours in Social Media by Looking at Conversational Threads

  2015cited by this paper
• Enquiring Minds: Early Detection of Rumors in Social Media from Enquiry Posts

  2015cited by this paper
• Towards Universal Paraphrastic Sentence Embeddings

  2015cited by this paper
• Detecting misinformation in online social networks using cognitive psychology

  2014cited by this paper
• Reading the riots on Twitter: methodological innovation for the analysis of big data

  2013influential reference
• Extra-Linguistic Constraints on Stance Recognition in Ideological Debates

  2013cited by this paper
• CROWDSOURCING A WORD–EMOTION ASSOCIATION LEXICON

  2013influential reference
• Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining

  2013influential reference
• Rumor has it: Identifying Misinformation in Microblogs

  2011cited by this paper
• Twitter under crisis: can we trust what we RT?

  2010cited by this paper
• Recognizing Stances in Online Debates

  2009cited by this paper
• Using the Revised Dictionary of Affect in Language to Quantify the Emotional Undertones of Samples of Natural Language

  2009cited by this paper
• The Rumour Bomb: Theorising the Convergence of New and Old Trends in Mediated US Politics

  2006cited by this paper
• Validiteit van de Nederlandse versie van de Linguistic Inquiry and Word Count (liwc)

  2005cited by this paper
• Long Short-Term Memory

  1997cited by this paper
• An argument for basic emotions

  1992influential reference
• English Speech Act Verbs: A Semantic Dictionary

  1987cited by this paper
• The Measurement of Meaning

  1958influential reference

• Unverified Rumor Detection

  2025cites this paper
• Efficient Processing of Long Sequence Text Data in Transformer: An Examination of Five Different Approaches

  2025cites this paper
• StanceEval 2024: The First Arabic Stance Detection Shared Task

  2024cites this paper
• Rumour Evaluation with Very Large Language Models

  2024cites this paper
• Automatic Feature Learning for Essence: a Case Study on Car Sequencing

  2024cites this paper
• Predicting rumor veracity on social media with cross-channel interaction of multi-task

  2024cites this paper
• Transformer-based models for combating rumours on microblogging platforms: a review

  2024cites this paper
• Connecting the dots between stance and fake news detection with blockchain, proof of reputation, and the Hoeffding bound

  2024cites this paper
• Enhancing prediction of user stance for social networks rumors

  2023cites this paper
• Review of stance detection for rumor verification in social media

  2023cites this paper
• A systematic review of machine learning techniques for stance detection and its applications

  2023influential citation
• Explainable Cross-Topic Stance Detection for Search Results

  2023cites this paper
• A Novel Rumor Detection Method Based on Non-Consecutive Semantic Features and Comment Stance

  2023cites this paper
• Emotion Detection for Misinformation: A Review

  2023cites this paper
• Enhancing stance detection through sequential weighted multi-task learning

  2023cites this paper
• Stanceosaurus: Classifying Stance Towards Multicultural Misinformation

  2022cites this paper
• Arabic fake news detection in social media Based on AraBERT

  2022cites this paper
• Rumor Stance Classification in Online Social Networks: The State-of-the-Art, Prospects, and Future Challenges

  2022influential citation
• Rumor Stance Classification in Online Social Networks: A Survey on the State-of-the-Art, Prospects, and Future Challenges

  2022cites this paper
• Arabic Fake News Detection: Comparative Study of Neural Networks and Transformer-Based Approaches

  2021cites this paper
• CIVIC-UPM at CheckThat! 2021: Integration of Transformers in Misinformation Detection and Topic Classification

  2021cites this paper
• Multi-Task Learning Framework for Stance Detection and Veracity Prediction

  2020cites this paper