Using natural language processing to connect with voters

You’ve probably heard that Cambridge Analytica, the data analytics firm hired by Trump’s campaign, used social media data mining techniques to understand the issues that mattered to the American public. This included details on voters’ identities, emails, friend networks, locations, and “likes”. With the use of this information, the 2016 presidential campaign was able to create tailored messages and precisely target audiences with its advertisements. Yet, only a tiny fraction of the users had agreed to release their information to a third party. 

Sounds bad, right? But what if I tell you that the 2012 Obama Presidential Election campaign also used AI for sentiment analysis to better understand public opinion. They mined Twitter data to gauge the sentiment of the voters towards certain policies and debates. The campaign also used data to determine which issues resonated with voters and what the electorate said about these issues.