Locality is a basic requirement for most modern methods for modelling systems of thousands of atoms or more. Despite its widespread use, the assumption of locality remains largely unfounded in the underlying quantum mechanical description. This work presents an algorithm for quantifying the locality of forces in a general molecular system. The algorithm was tested on linear hydrocarbon systems; it confirmed the locality of the tight-binding model DFTB and quantified the extent to which chemical changes, such as bond conjugation and oxygen addition, introduce long-range effects within the more accurate DFT model. The results motivated the development of an intramolecular hydrocarbon potential using the GAP machine learning method; the new potential is a promising alternative to existing models used in hydrocarbon simulation.