Recently, FIFA World Cup 2014 has just started. During the inaugural match between Brazil and Croatia, many people were tweeting about the match using Twitter especially when goals are produced in the match. You will know it once you see the dashboard created by CartoDB here: http://cartodb.com/v/worldcup/brazil-croatia/#/2/24.7/-7.0/0
Above: The dashboard created by CartoDB.
After seeing this dashboard, you will feel that "Wow! Dashboard can help us to analyse who are watching football!". But before developing a dashboard, one has to collect the data produced. In this case, the data are the people who have tweeted about this football match. This shows that which part of the world are great fans of football and which are not. As you can see from this dashboard example, most of the football fans are from Europe, Southeast Asia, North and South America.
So, what can we refer from this example? This example tells us that with social network & its produced data related to mining industries/mill products, we can create dashboard in helping the mining industries to find out which part of the world are in demand for mining materials or mill products with reference from the visualization of the dashboard.
In conclusion, with social analytics, it helps mining industries to find out which part of the world are in high demand for mining materials or mill products due to the data produced from social network. Indeed, social analytics is also part of business intelligence.