Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.
Customer signals
- Publication category
- Other algorithms
- Impact assessment
- Field not filled in.
- Status
- In use
General information
Theme
Begin date
Contact information
Link to publication website
Link to source registration
Responsible use
Goal and impact
PURPOSE: Targeted improvement of group-wide services, products, processes and services
IMPACT: The algorithm is used to improve service delivery in a general sense. The results have no impact on the (un)equal treatment of individual citizens.
Considerations
The application provides better services (lower costs and higher satisfaction). Possible personal data in the data is masked.
Human intervention
There is always human intervention between the outcomes of the algorithms and the actions taken because the outcomes serve as input for improvement teams within the municipality.
Risk management
N/A
Legal basis
Justified interest: improving services
Operations
Data
Technical design
A text mining algorithm is used to bundle the signals from Rotterdammers into one set of signals and extract improvement actions from them. This algorithm was developed by Underlined. The algorithm is used to convert open text fields into categories, also known as topic modelling. The algorithm maps both topics and perceptions. Each text is provided with up to 3 main topics and with up to 3 sub-topics each by this text mining algorithm for both dimensions. Input comes from various sources within the municipality (e.g. callback notes, customer satisfaction surveys and complaints). This involves well over 100,000 texts annually, which can be uniformly and quickly categorised in this way.
External provider
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