Sentiment analysis of financial news using unsupervised approach

Abstract

Sentiment analysis aims to determine the sentiment strength from a textual source for good decision making. This work focuses on application of sentiment analysis in financial news. The semantic orientation of documents is first calculated by tuning the existing technique for financial domain. The existing technique is found to have limitations in identifying representative phrases that effectively capture the sentiment of the text. Two alternative techniques - one using Noun-verb combinations and the other a hybrid one, are evaluated. Noun-verb approach yields best results in the experiment conducted.