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Detecting Latent Ideology in Expert Text: Evidence From Academic Papers in Economics

机译:在专家文本中检测潜在思想:经济学中的学术论文证据

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Previous work on extracting ideology from text has focused on domains where expression of political views is expected, but it's unclear if current technology can work in domains where displays of ideology are considered inappropriate. We present a supervised ensemble n-gram model for ideology extraction with topic adjustments and apply it to one such domain: research papers written by academic economists. We show economists' political leanings can be correctly predicted, that our predictions generalize to new domains, and that they correlate with public policy-relevant research findings. We also present evidence that unsupervised models can under-perform in domains where ideological expression is discouraged.
机译:从文本中提取思想的以前的工作都集中在预期政治观点的表达的域名,但目前尚不清楚当前技术是否可以在认为意识形态的域名被认为是不合适的域名。 我们提出了一个有关主题调整的思想提取的监督集合N-Gram模型,并将其应用于一个这样的领域:学术经济学家撰写的研究论文。 我们展示了经济学家的政治倾向,可以正确预测,我们的预测概括了新领域,以及他们与公共政策相关的研究结果相关。 我们还提出了证据表明,无监督的模型可以在暗示暗示思想表达的域中进行。

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