Lexicon Creation for Financial Sentiment Analysis using Network Embedding

Abstract

It is necessary to build a comprehensive polarity dictionary specialized for financial policy to improve the accuracy of lexicon-based sentiment analysis in evaluating texts written on financial policy. In this research, we acquire distributed representation of words using feature learning of dependency network of words and create the polarity dictionary by bootstrap method using the distributed representation of words.