ニュース記事分析によるトピック・銘柄の関係知識獲得

抄録

In this study, we propose a method that acquires a topic dictionary from financial news articles. The topic dictionary is the knowledge related to the stock brands, and is composed of topics (e.g. influenza), groups of stock brands (e.g. pharmaceutical companies and / or spinning companies), and the strength of relations between them. The strength of a relation is updated by referring to the number of news headlines of the topic and the volume of transaction of the stock, and is used in order to strengthen the relation by calculating the weighted sum of news headlines. This study shows the correlation coefficient between the weighted sum of transactions and the volume is higher than the one between the non-weighted sum and the volume of transactions. The topic dictionary is expected to help catching the influence which newest topics give to the volume of transactions.