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2017 ACL ACL 2017

Demographic Inference on Twitter using Recursive Neural Networks

AbstractIn social media, demographic inference is a critical task in order to gain a better understanding of a cohort and to facilitate interacting with one’s 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.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Interdisciplinary
📈 Trend Setter - Multi-View Learning

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