History playground: A tool for discovering temporal trends in massive textual corpora.

Recent studies have shown that macroscopic patterns of continuity and change over the course of centuries can be detected through the analysis of time series extracted from massive textual corpora. Similar data-driven approaches have already revolutionized the natural sciences and are widely believe...

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Publicado en:Digital Scholarship in the Humanities Vol. 35; no. 2; pp. 328 - 342
Autores principales: Lansdall-Welfare, Thomas, Cristianini, Nello
Formato: Artículo
Publicado: Oxford University Press / USA Jun2020
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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        atl: History playground: A tool for discovering temporal trends in massive textual corpora.
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        au:
          Lansdall-Welfare, Thomas
          Cristianini, Nello
        affil: Intelligent Systems Laboratory , Department of Engineering Mathematics, University of Bristol, Bristol, UK
      su:
        User interfaces
        Corpora
        Digitization
        Playgrounds
        Standardization
        Algorithms
      sug:
        subj:
          User interfaces
          Corpora
          Digitization
          Playgrounds
          Standardization
          Algorithms
      ab: Recent studies have shown that macroscopic patterns of continuity and change over the course of centuries can be detected through the analysis of time series extracted from massive textual corpora. Similar data-driven approaches have already revolutionized the natural sciences and are widely believed to hold similar potential for the humanities and social sciences, driven by the mass-digitization projects that are currently under way, and coupled with the ever-increasing number of documents which are 'born digital'. As such, new interactive tools are required to discover and extract macroscopic patterns from these vast quantities of textual data. Here we present History Playground, an interactive web-based tool for discovering trends in massive textual corpora. The tool makes use of scalable algorithms to first extract trends from textual corpora, before making them available for real-time search and discovery, presenting users with an interface to explore the data. Included in the tool are algorithms for standardization, regression, change-point detection in the relative frequencies of n-grams, multi-term indices, and comparison of trends across different corpora.
      pubtype: Academic Journal
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    language: English
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