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Vigi4Med Scraper: A Framework for Web Forum Structured Data Extraction and Semantic Representation

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  • Bissan Audeh
  • Michel Beigbeder
  • Antoine Zimmermann
  • Philippe Jaillon
  • Cédric Bousquet

Abstract

The extraction of information from social media is an essential yet complicated step for data analysis in multiple domains. In this paper, we present Vigi4Med Scraper, a generic open source framework for extracting structured data from web forums. Our framework is highly configurable; using a configuration file, the user can freely choose the data to extract from any web forum. The extracted data are anonymized and represented in a semantic structure using Resource Description Framework (RDF) graphs. This representation enables efficient manipulation by data analysis algorithms and allows the collected data to be directly linked to any existing semantic resource. To avoid server overload, an integrated proxy with caching functionality imposes a minimal delay between sequential requests. Vigi4Med Scraper represents the first step of Vigi4Med, a project to detect adverse drug reactions (ADRs) from social networks founded by the French drug safety agency Agence Nationale de Sécurité du Médicament (ANSM). Vigi4Med Scraper has successfully extracted greater than 200 gigabytes of data from the web forums of over 20 different websites.

Suggested Citation

  • Bissan Audeh & Michel Beigbeder & Antoine Zimmermann & Philippe Jaillon & Cédric Bousquet, 2017. "Vigi4Med Scraper: A Framework for Web Forum Structured Data Extraction and Semantic Representation," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-18, January.
    • Handle: RePEc:plo:pone00:0169658
    DOI: 10.1371/journal.pone.0169658
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    Cited by:

    1. Bissan Audeh & Florelle Bellet & Marie-Noëlle Beyens & Agnès Lillo-Le Louët & Cédric Bousquet, 2020. "Use of Social Media for Pharmacovigilance Activities: Key Findings and Recommendations from the Vigi4Med Project," Drug Safety, Springer, vol. 43(9), pages 835-851, September.

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