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Industrial Memories: Exploring the Findings of Government Inquiries with Neural Word Embedding and Machine Learning

  • Susan LeavyEmail author
  • Emilie Pine
  • Mark T. Keane
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11053)

Abstract

We present a text mining system to support the exploration of large volumes of text detailing the findings of government inquiries. Despite their historical significance and potential societal impact, key findings of inquiries are often hidden within lengthy documents and remain inaccessible to the general public. We transform the findings of the Irish government’s inquiry into industrial schools and through the use of word embedding, text classification and visualization, present an interactive web-based platform that enables the exploration of the text to uncover new historical insights. Code related to this paper is available at: https://industrialmemories.ucd.ie.

Keywords

Word embeddings Text classification Visualization Government inquiry reports 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University College DublinDublinIreland

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