Bjarke Felbo

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Mobile phone metadata are increasingly used to study human behavior at largescale. In developing countries, where data is scarce, data generated by mobile phones have already helped with planning disaster response and informing public health policy. Basic demographic information such as age or gender is, however, often missing from mobile phone data. There(More)
NLP tasks are often limited by scarcity of manually annotated data. In social media sentiment analysis and related tasks, researchers have therefore used binarized emoticons and specific hashtags as forms of distant supervision. Our paper shows that by extending the distant supervision to a more diverse set of noisy labels, the models can learn richer(More)
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