  We propose an indicator to measure the degree to which a particular news
article is novel, as well as an indicator to measure the degree to which a
particular news item attracts attention from investors. The novelty measure is
obtained by comparing the extent to which a particular news article is similar
to earlier news articles, and an article is regarded as novel if there was no
similar article before it. On the other hand, we say a news item receives a lot
of attention and thus is highly topical if it is simultaneously reported by
many news agencies and read by many investors who receive news from those
agencies. The topicality measure for a news item is obtained by counting the
number of news articles whose content is similar to an original news article
but which are delivered by other news agencies. To check the performance of the
indicators, we empirically examine how these indicators are correlated with
intraday financial market indicators such as the number of transactions and
price volatility. Specifically, we use a dataset consisting of over 90 million
business news articles reported in English and a dataset consisting of
minute-by-minute stock prices on the New York Stock Exchange and the NASDAQ
Stock Market from 2003 to 2014, and show that stock prices and transaction
volumes exhibited a significant response to a news article when it is novel and
topical.
