OSM processes over 3.1 million feature changes per day. With the help of OSMCha and the ever-vigilant OSM community, many low-quality changes are found and corrected. However, sometimes low-quality labels are not detected and slip into the map.

Towards ensuring a high-quality map, I have been applying natural language processing (NLP) techniques to detect low-quality labels. Part of applying these NLP techniques requires:

1. Defining low-quality labels and understanding their properties
2. Determining the motivation of a user who submits a low-quality label

First, towards defining a low-quality label, we typically think of labels that include profanity, such as the following (also! 🙂, all of the screenshots you see below are examples of low-quality labels that I have found with my filtering logic):

Profane label says: “The Shit”

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