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Data mining and NLP for Processing Social Offers of a National Aid Organization

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  • Senst, Benjamin

Abstract

For large organisations with numerous organisational units, it can be challenging to keep track of individual events. In a joint project by Data Science for Social Good Berlin e.V. and the Data Science Hub of the German Red Cross, social services were processed over several phases between summer 2022 and summer 2024 using new technologies such as web scraping, data engineering, and natural language processing, and their implementation in various user applications was tested. More than 600,000 web documents were collected and more than 30,000 offers were identified. The results of this automated method were compared with the existing data set. Web scraping and subsequent processing are suitable for at least supplementing the previous approach. Web scraping, NLP, and data engineering offer large organisations the opportunity to effectively gain an overview of local events.

Suggested Citation

  • Senst, Benjamin, 2024. "Data mining and NLP for Processing Social Offers of a National Aid Organization," SocArXiv 3pd4s, Center for Open Science.
    • Handle: RePEc:osf:socarx:3pd4s
    DOI: 10.31219/osf.io/3pd4s
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