Blog
16/11/2023
Concept mapping is a method developed by Trochim (1989) for visualizing and analyzing the shared representation held by a group of actors of a given issue. It is notably used in the academic and public sectors to help understand complex issues, contribute to consensus-building and support decision-making. Nevertheless, analyzing data from a concept mapping workshop often requires programming and statistical analysis skills.
“Polygon is developing a Python based open source package that will facilitate the analysis of concept maps.”
To carry out this step, we are developing at Polygon a Python based open source package that will facilitate the analysis of concept maps. It will include all the functionalities needed to carry out this type of analysis using the latest advances proposed by Péladeau et al. (2017) and Polygon (read articles: An alternative approach to the concept mapping method: clustering analysis on original distances & Dimensionality reduction: Alternative approaches for concept mapping).
This library includes the following features:
- data cleansing utilities
- distance matrix calculation
- identification and removal of outliers
- partitioning of concepts by hierarchical clustering
- cluster validity assessment using selected indicators
- recommendation of the most appropriate number of clusters
- projection into a reduced space using nonlinear dimensionality reduction methods
- generation of concept maps and GoZone plots
The library will be available on Pypi, the Python library distribution platform. The source code will also be accessible on Polygon’s GitHub account. This will enable researchers around the world to easily access our tool and use it in their scientific projects. Similarly, this library will be fully documented to facilitate its use, but also to help understand the general method. We look forward to sharing our tool with the scientific community and contributing to the advancement of this field of research. More information on the design and release schedule for this library will be announced shortly.
Bibliography:
Péladeau, N., Dagenais, C., & Ridde, V. (2017). Concept mapping internal validity: A case of misconceived mapping? Evaluation and Program Planning, 62, 56–63. https://doi.org/10.1016/j.evalprogplan.2017.02.005
Trochim, W. M. (1989). An introduction to concept mapping for planning and evaluation. Evaluation and Program Planning, 12 (1), 1–16. https://doi.org/10.1016/0149-7189(89)90016-5
Concept Mapping Tool
Participatory research
Research methods
Python
Open source
