2018 EMNLP EMNLP 2018

Cross-Lingual Cross-Platform Rumor Verification Pivoting on Multimedia Content

Abstract

AbstractWith the increasing popularity of smart devices, rumors with multimedia content become more and more common on social networks. The multimedia information usually makes rumors look more convincing. Therefore, finding an automatic approach to verify rumors with multimedia content is a pressing task. Previous rumor verification research only utilizes multimedia as input features. We propose not to use the multimedia content but to find external information in other news platforms pivoting on it. We introduce a new features set, cross-lingual cross-platform features that leverage the semantic similarity between the rumors and the external information. When implemented, machine learning methods utilizing such features achieved the state-of-the-art rumor verification results.

🌉 Interdisciplinary Bridge — Computer Science and Machine Learning and Natural Language Processing
📈 Trend Setter — Multi-Lingual Learning
🧭 Keyword Pioneer — rumor verification
🐣 Hot Topic Early Bird — misinformation detection
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio