Fine-grained analysis of explicit and implicit sentiment in financial news articles
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.
financial news automatic sentiment analysis