FAQ: Analyzing Social Data to Understand the US Electorate

Our analytics engine Kairos processes unstructured data from millions of sites, blogs, and social platforms like Twitter and Tumblr. Billions of public posts are then analyzed and classified across 25,000 topics, emotions, and demographics--turning noisy social data into insights. In order to create predictions around the elections using our analytics platform Kairos, we built 4 metrics: Awareness, Positivity, Negativity and Intent, of which only Negativity and Intent proved to be valuable in predicting elections. Negativity and Intent are natural language processing classifiers which take advantage of sentence structure as well as keyword matching. Then we modeled the data against survey polls, primary results, and survey pools to obtain weights of influence for each of the social indices.