Case Study: Rappler achieves deeper election insights and richer political profiles with Ontotext GraphDB

Rappler Created the First Philippine Politics Knowledge Graph by Using Ontotext GraphDB

Rappler, the Philippine digital-native news group founded by Nobel Prize winner Maria Ressa, wanted to deliver more complex political and election information and support deeper analysis of events. Using Ontotext GraphDB, Rappler set out to model the country’s highly complex political and electoral system, despite challenges such as a small newsroom team, sparse local candidate data, and the need to generate nearly 50,000 public-facing pages.

Ontotext helped Rappler build the first Philippine Politics Knowledge Graph and ontology, combining Rappler’s research data with GraphDB inferencing and natural language generation to create profiles for 83 national candidates, 46,165 local candidates, and 1,732 locales. The result was richer election coverage, better historical and future data analysis, and the ability to uncover hidden relationships in disinformation topics, actors, and trends while preserving factual accuracy.

Rappler

Gemma Bagayaua-Mendoza

Head of Digital Services and Lead Researcher for Disinformation and Platforms