Abstract: A prediction system can predict future trending topics. The prediction system can classify social media posts by region and vertical, extract text from the posts, tokenize the extracted text, and organizing the tokens into n-grams. The prediction system can store the n-grams from the posts in a cumulative set of n-grams, with each n-gram tagged with the originating post's identified region, vertical, and a time value. The prediction system can compute, for each n-gram, a frequency within each category defined by a region/vertical pair. The prediction system can fit occurrence data for n-grams to a polynomial and identify the slope of the point on for the current time. The slope can be used as a prediction of growth or decline for the n-gram. The prediction system can identify n-grams with a comparatively large slope within that region/vertical as likely to be trending in the future.

Abstract: A prediction system can predict future trending topics. The prediction system can classify social media posts by region and vertical, extract text from the posts, tokenize the extracted text, and organizing the tokens into n-grams. The prediction system can store the n-grams from the posts in a cumulative set of n-grams, with each n-gram tagged with the originating post's identified region, vertical, and a time value. The prediction system can compute, for each n-gram, a frequency within each category defined by a region/vertical pair. The prediction system an fit occurrence data for n-grams to a polynomial and identify the slope of the point on for the current time. The slope can be used as a prediction of growth or decline for the n-gram. The prediction system can identify n-grams with a comparatively large slope within that region/vertical as likely to be trending in the future.