The modern political landscape is full of division. This is nothing new, and there have always been a number of factors contributing to the cut and thrust of political discourse. But today, political sentiment is influenced by more dynamic and immediate forces that can be used as tools in the information war. Traditional modes of communication, such as print media, political campaigns and advertisements are, of course, still prominent, but the modern information landscape contains the added variables of the web and, more significantly, social media.
We are now in an age in which sentiment on any number of topics can be uncovered through the analysis of enormous amounts of data, ranging from the traditional, such as polls, election results and expert analysis, to alternative data sets, such as social media platforms. To ensure we get a true picture of any sentiment, however, we must be confident that the information we analyze is credible, which is becoming increasingly difficult to identify. As a data scientist with extensive experience in building sentiment models using natural language processing (NLP), I’d like to share my experience in uncovering the truth in today’s increasingly challenging information landscape.