Polarity Assignment to Causal Information Extracted from Financial Articles Concerning Business Performance of Companies

Abstract

We propose a method of assigning polarity to causal information extracted from Japanese financial articles concerning business performance of companies. Our method assigns polarity (positive or negative) according to business performance to causal information, e.g. “zidousya no uriage ga koutyou: (Sales of cars are good)” (The polarity positive is assigned in this example.). First, our method classifies articles concerning business performance into positive articles and negative articles. Using this classified sets of articles, our method assigns polarity (positive or negative) to causal information extracted from the set of articles concerning business performance. We evaluated our method and it attained 75.3% precision and 47.9% recall of assigning polarity positive, and 77.0% precision and 58.5% recall of assigning polarity negative, respectively.