- CMT id: 296
- Abstract: Mobile phone metadata are increasingly used to study human behavior at large-scale. There has recently been a growing interest in predicting demographic information from metadata. Previous approaches relied on hand-engineered features. We here apply, for the first time, deep learning methods to mobile phone metadata using a convolutional network. Our method provides high accuracy on both age and gender prediction. These results show great potential for deep learning approaches for prediction tasks using standard mobile phone metadata.
- Conflicts: mit.edu, dtu.dk, harvard.edu, ku.dk, telenor.com, telenor.no