CAIRN-INT.INFO : International Edition

The 2017 legislative elections brought an unprecedented breath of fresh air into the Fifth Republic, marking the arrival of many new faces in politics. How did these newly elected officials, many of whom were unusual recruits, adapt to such a highly codified space? This question is difficult to answer, given that parliamentary activity has many facets that traditional research methods struggle to account for in a global fashion. In order to describe the diverse forms of parliamentary engagement from a relational perspective, this article introduces the concept of self-organizing maps (SOMs) to reduce dimensionality. After explaining the principles of SOMs, this article will highlight their value in analyzing the parliamentary engagement of the new crop of legislators elected in 2017. Comparing SOMs with a geometrical data analysis underscores the former’s value with regard to permitting a granular analysis of parliamentary praxis. More broadly, this text will demonstrate that self-organizing maps can be a useful statistical tool, whether they are employed to reduce and visualize a large data set or to represent a social space.

  • political sphere
  • machine learning
  • parliament
  • freshmen
  • new elected officials
  • dimensionality reduction
Julien Boelaert
Étienne Ollion
This is the latest publication of the author on cairn.
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