Many social and physical processes (e.g., crime, conflict, social media activity, financial markets, new product adoption, social network communication, earthquakes, neural spiking, disease spread) produce event point patterns that exhibit clustering. Hawkes, or self-exciting point process, models are a popular choice for modeling the clustering patterns which can be driven by both exogenous influences and endogenous forces like contagion/self-excitement. These models stipulate that each event can be triggered by past events creating a branching structure that produces the endogenous clustering. The contagion effects are modeled by a shot-noise term which aggregates the influence of past events to temporarily increase the event rate following each event. This talk will introduce the hawkes process and illustrate some extensions and uses of hawkes models in three areas: (i) modeling contagion in terrorist attacks, (ii) incorporating near-repeat effects to forecasting crime hotspots (winning performance in the NIJ Crime Forecasting Challenge), (iii) using mutually exciting hawkes processes to identify social influence in Yelp restaurant reviews.