Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Texts

Understand

The use of robo-readers to analyze news texts is an emerging technology trend in computational finance.

• In recent research, a substantial effort has been invested to develop sophisticated financial polarity-lexicons that can be used to investigate how financial sentiments relate to future company performance.
• However, based on experience from other fields, where sentiment analysis is commonly applied, it is well-known that the overall semantic orientation of a sentence may differ from the prior polarity of individual words.
• The objective of this article is to investigate how semantic orientations can be better detected in financial and economic news by accommodating the overall phrase-structure information and domain-specific use of language.