Mapping and modelling the crime perception gap

Peoples perception of crime risk does not always coincide with the actual situation. This disparity is known as the crime perception gap (CPG) and may have repercussions on peoples lifestyle, social behaviour, and the spatial and economic dynamic. Narrowing this gap is needed to improve peoples quality of life. Further research could delineate where the gap exists in space and relate it with other relevant information in order to ease the decision-making in the design of targeted strategies. The project will test the following hypotheses about CPG: Hypothesis 1: People misconceive crime reality in two directions. First, they may believe that low- crime rate areas are unsafe. Second, they may believe that high-crime rate areas are safe. Hypothesis 2: People perceive areas as unsafe (or safe) because their neighbouring areas may be unsafe (or safe). Thus, crime reality seems to have an inaccurate diffusing effect on the perception of adjacent areas. Hypothesis 3: People are more likely to perceive an area as unsafe if they know that area but it is not within areas of their regular and daily activities. Thus, frequently visited and very familiar places are perceived (or misconceived) as safer. To understand what factors (spatial, socio-economic, and demographic) relate to crime perception risk we will conduct a literature review and interview experts in the field. Our perceptual data will be collected via online and face-to-face surveys on a GIS-based sketch mapping web user interface. To understand the relationship between the factors that affect crime risk perception and the perceptions we will use statistical and machine learning methods. Furthermore, the perceptions and real crime events will be analysed to detect the gap in space (i.e. areas with a mismatch between crime reality and perceptions) using geoprocessing, spatial statistical methods, and classification accuracy metrics. Last, we will develop a Geovisual Analytics environment (i.e. a web interface to interactively analyse and visualize geographical information) for the exploration of the crime perception gap. Our key objective is to identify the factors, and especially the spatial factors, that may relate to and affect crime risk perception, but also explore the how and to what degree they affect it. Also, our analysis will be applied in two urban areas of different countries to examine if perceptual findings are bounded to cultural settings (i.e. Austria and Hungary). Additionally, during our project we will develop two web user interfaces (i.e. the Sketch Mapping and the Geovisual Analytics) that can be used to further explore perceptual gaps in space or be used for other kinds of geographical research.