Forecasting location-based events with spatio-temporal storytelling

Abstract

Storytelling, the act of connecting entities through relationships, provides an intuitive platform for exploratory analysis. This paper combines storytelling and Spatio-logical Inference (SLI) to generate rules of interaction among entities and measure how well they forecast a real-world event. The proposed algorithm first takes as input the probability of prior occurrences of events along with their spatial distances. It calculates their soft truths, i.e., the belief they have indeed been observed with certainty. Subsequently, the algorithm applies a relaxed form of logical conjunction and disjunction to compute a distance to satisfaction for each rule. The rules of lowest distances represent the best forecasts. Extensive experiments with social unrest in Afghanistan show that storytelling and SLI can outperform common probabilistic approaches by as much as 30% in terms of precision and 13% in terms of recall.