Language and Domain Specificity: A Chinese Financial Sentiment Dictionary
نویسندگان
چکیده
Abstract We use Word2vec to develop a financial sentiment dictionary from 3.1 million Chinese-language news articles. Our maps semantically similar words subset of human-expert generated words. In validation tests, our scores the articles consistently with human reading full return association outperforms and subsumes previous Chinese dictionaries, such as direct translations Loughran McDonald’s (2011, Journal Finance, 66, 35–65) English-language dictionary. also generate list politically related positive that is unique China; we find this has weaker returns than does other demonstrate state media uses more fewer negative words, exhibits bias. This bias renders media’s less return-informative. findings dictionary-based analysis strong language domain specificity.
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ژورنال
عنوان ژورنال: Review of Finance
سال: 2021
ISSN: ['1875-824X', '1572-3097']
DOI: https://doi.org/10.1093/rof/rfab036