Journal of Big Data (Oct 2023)

Open framework for analyzing public parliaments data

  • Shai Berkovitz,
  • Amit Mazuz,
  • Michael Fire

DOI
https://doi.org/10.1186/s40537-023-00831-3
Journal volume & issue
Vol. 10, no. 1
pp. 1 – 22

Abstract

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Abstract Open information about government organizations should interest all citizens who care about their governments’ functionality. Large-scale open governmental data open new opportunities for citizens and researchers to monitor their government’s activities and improve its transparency. Over the years, various projects and systems have processed and analyzed governmental data based on open government information. Here, we present the Collecting and Analyzing Parliament Data (CAPD) framework. This novel generic open framework enables collecting and analyzing large-scale public governmental data from multiple sources. This study utilized our framework to collect over 64,000 parliament protocols from over 90 committees from three countries and analyzed it to calculate structured features. Next, we utilized anomaly detection and time series analysis to achieve a number of insights into the committees’ activities. This study demonstrates that the CAPD framework can be utilized to effectively identify anomalous meetings and detect dates of events that affect the parliaments’ functionality and help to monitor their activities.

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