The ONTOLISST project and its preliminary results on using NLP for automated topic assignment

This presentation introduces the ONTOLISST project and describes its first experiments related to AI-based metadata assignment using Natural Language Processing (NLP) tools to annotate topics on social science survey data that have been documented using the Data Document Initiative (DDI) metadata standards. The slides were presented in the webinar Intelligence artificielle et métadonnées en SHS organised by CDSP on February 10, 2025. The webinar was part of the 2025 edition of the International Love Data Week. Webinar recording is also available.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-08-11
DOI
https://doi.org/10.5281/zenodo.16794476
Primary Topic
Computational and Text Analysis Methods
Type
article
Field-Weighted Citation Impact
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article

The ONTOLISST project and its preliminary results on using NLP for automated topic assignment

Zenodo (CERN European Organization for Nuclear Research)
Computational and Text Analysis Methods
article

The ONTOLISST project and its preliminary results on using NLP for automated topic assignment

article en

Abstract

This presentation introduces the ONTOLISST project and describes its first experiments related to AI-based metadata assignment using Natural Language Processing (NLP) tools to annotate topics on social science survey data that have been documented using the Data Document Initiative (DDI) metadata standards. The slides were presented in the webinar Intelligence artificielle et métadonnées en SHS organised by CDSP on February 10, 2025. The webinar was part of the 2025 edition of the International Love Data Week. Webinar recording is also available.

Zenodo (CERN European Organization for Nuclear Research)
Tampere University (FI), Centre for Social Sciences (HU), Hungarian Academy of Sciences (HU)
Quality Education
Openalex Percentile: Top 41%
Computational and Text Analysis Methods
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