2017
ACL
ACL 2017
Demographic Inference on Twitter using Recursive Neural Networks
Abstract
AbstractIn social media, demographic inference is a critical task in order to gain a better understanding of a cohort and to facilitate interacting with oneβs audience. Most previous work has made independence assumptions over topological, textual and label information on social networks. In this work, we employ recursive neural networks to break down these independence assumptions to obtain inference about demographic characteristics on Twitter. We show that our model performs better than existing models including the state-of-the-art.
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Interdisciplinary Bridge
β Deep Learning and Interdisciplinary and Machine Learning
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Trend Setter
β Multi-View Learning
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Keyword Pioneer
β demographic inference
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Cross-Pollinator
β 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