  In an increasingly connected global market, news sentiment towards one
company may not only indicate its own market performance, but can also be
associated with a broader movement on the sentiment and performance of other
companies from the same or even different sectors. In this paper, we apply NLP
techniques to understand news sentiment of 87 companies among the most reported
on Reuters for a period of seven years. We investigate the propagation of such
sentiment in company networks and evaluate the associated market movements in
terms of stock price and volatility. Our results suggest that, in certain
sectors, strong media sentiment towards one company may indicate a significant
change in media sentiment towards related companies measured as neighbours in a
financial network constructed from news co-occurrence. Furthermore, there
exists a weak but statistically significant association between strong media
sentiment and abnormal market return as well as volatility. Such an association
is more significant at the level of individual companies, but nevertheless
remains visible at the level of sectors or groups of companies.
