Fine-grained analysis of explicit and implicit sentiment in financial news articles
作者：
Highlights：
• In the financial domain, news has an impact on the stock markets.
• Most sentiment analysis methods are coarse-grained and focus on explicit sentiment.
• Such a method is insufficient to detect topic-specific sentiment in financial news articles.
• We propose a novel fine-grained method that detects explicit and implicit sentiment.
• This is a viable method for topic-specific sentiment analysis in financial news text.
摘要
•In the financial domain, news has an impact on the stock markets.•Most sentiment analysis methods are coarse-grained and focus on explicit sentiment.•Such a method is insufficient to detect topic-specific sentiment in financial news articles.•We propose a novel fine-grained method that detects explicit and implicit sentiment.•This is a viable method for topic-specific sentiment analysis in financial news text.
论文关键词：Automatic sentiment analysis,Financial news
论文评审过程：Available online 14 February 2015.
论文官网地址：https://doi.org/10.1016/j.eswa.2015.02.007
