论文标题
经济学数据科学
Data Science in Economics
论文作者
论文摘要
本文提供了经济学数据科学艺术的状态。通过对数据科学的应用和方法进步的新分类学进行了新的分类学。数据科学的进步将在三个单独的深度学习模型，集合模型和混合模型中进行研究。应用领域包括股票市场，营销，电子商务，公司银行业务和加密货币。 Prisma方法，一种系统的文献综述方法来确保调查的质量。研究结果表明，趋势是在混合模型的发展上，因为超过51％的审查文章应用的混合模型。另一方面，发现基于RMSE的精度度量，混合模型的预测准确性比其他算法更高。虽然预计趋势朝着深度学习模型的进步发展。
This paper provides the state of the art of data science in economics. Through a novel taxonomy of applications and methods advances in data science are investigated. The data science advances are investigated in three individual classes of deep learning models, ensemble models, and hybrid models. Application domains include stock market, marketing, E-commerce, corporate banking, and cryptocurrency. Prisma method, a systematic literature review methodology is used to ensure the quality of the survey. The findings revealed that the trends are on advancement of hybrid models as more than 51% of the reviewed articles applied hybrid model. On the other hand, it is found that based on the RMSE accuracy metric, hybrid models had higher prediction accuracy than other algorithms. While it is expected the trends go toward the advancements of deep learning models.
