Many investment companies in the U.S. and Europe have been using news analytics to improve the quality of its business. Interest in news analytics is related to the ability to predict changes of prices, volatility and trading volume on the stock market. We consider different volatility models augmented with news analytics data to examine the impact of news intensity on stock volatility. The study shows that the problem of examining the impact of news intensity on volatility is far more involveed than it might seem at first sight. The study shows that the addition of news intensity or contemporaneous trading volume increases the explanatory power of standard models. The augmented models illustrated here show potential for more accurate prediction of volatility which, in turn, can lead to better risk management.