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

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Vigi4Med Scraper is an open-source tool that extracts and anonymizes data from web forums for analysis. It structures data into Resource Description Framework (RDF) graphs, aiding in adverse drug reaction detection.

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Area of Science:

  • Data Science
  • Computational Linguistics
  • Pharmacovigilance

Background:

  • Information extraction from social media is crucial for data analysis but presents challenges.
  • Web forums are rich sources of user-generated data relevant to various domains.

Purpose of the Study:

  • To introduce Vigi4Med Scraper, a configurable, open-source framework for structured data extraction from web forums.
  • To enable anonymized data representation in Resource Description Framework (RDF) graphs for enhanced data analysis and semantic linking.
  • To support the Vigi4Med project's goal of detecting adverse drug reactions (ADRs) from social networks.

Main Methods:

  • Developed a highly configurable framework allowing users to specify data extraction parameters via a configuration file.
  • Implemented data anonymization and representation using RDF graphs for semantic interoperability.
  • Integrated a proxy with caching to manage request rates and prevent server overload.

Main Results:

  • Successfully extracted over 200 gigabytes of data from more than 20 distinct websites.
  • Demonstrated the framework's generic applicability across various web forums.
  • Established a foundation for the Vigi4Med project's ADR detection capabilities.

Conclusions:

  • Vigi4Med Scraper provides a robust and flexible solution for extracting and structuring web forum data.
  • The RDF representation facilitates advanced data analysis and integration with existing semantic resources.
  • The framework is a significant first step towards leveraging social media data for pharmacovigilance.