FinLex: An effective use of word embeddings for financial lexicon generation

The Journal of Finance and Data Science(2022)

引用 5|浏览27
暂无评分
摘要
We present a simple and effective methodology for the generation of lexicons (word lists) that may be used in natural language scoring applications. In particular, in the finance industry, word lists have become ubiquitous for sentiment scoring. These have been derived from dictionaries such as the Harvard Inquirer and require manual curation. Here, we present an automated approach to the curation of lexicons, which makes automatic preparation of any word list immediate. We show that our automated word lists deliver comparable performance to traditional lexicons on machine learning classification tasks. This new approach will enable finance academics and practitioners to create and deploy new word lists in addition to the few traditional ones in a facile manner.
更多
查看译文
关键词
Lexicons,Embeddings,Scoring,Machine learning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络