Abstract:
In the last years the use of social networks has increased, spreading all over the world. People feel free to express their opinion and this can be potentially useful to understand what they think about a particular topic and how it is connected to what official newspaper publish about it.
The aim of this work is to analyse the sentiment of Twitter users about president Trump statements on trade tariffs starting from the 26th of July. The tweets considered in this work, are written only in English and must contain at least one of these hashtag: #TrumpTariffs, #TradeNotAid, #TradeWar and #Trump#EU (two different hashtag, but taken together).
This analysis will be integrated considering also articles published by the main newspapers of economy and politics. After a first part of text mining, there will be a second on data mining to recognise if there are relationships between what are the results of the analysis and the path of the economy.
