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  This dataset contains two manually pre-labeled datasets:
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- In the audience dataset, we labeled 6,205 randomized sentences from the Fed database as speaking either about households, firms, the financial sector, the government, or the central bank itself.
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- In the sentiment dataset, we labeled 6,683 sentences from the Fed database, which are either labeled as being positive (1) or negative (0).
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  The datasets were used to train an [audience classifier](Moritz-Pfeifer/CentralBankRoBERTa-audience-classifier) and a [sentiment classifier](https://huggingface.co/Moritz-Pfeifer/CentralBankRoBERTa-sentiment-classifier).
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  ---
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  This dataset contains two manually pre-labeled datasets:
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+ In the **audience dataset**, we labeled 6,205 randomized sentences from the Fed database as speaking either about households, firms, the financial sector, the government, or the central bank itself.
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+ In the **sentiment dataset**, we labeled 6,683 sentences from the Fed database, which are either labeled as being positive (1) or negative (0).
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  The datasets were used to train an [audience classifier](Moritz-Pfeifer/CentralBankRoBERTa-audience-classifier) and a [sentiment classifier](https://huggingface.co/Moritz-Pfeifer/CentralBankRoBERTa-sentiment-classifier).
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