Logo do repositório
 
Publicação

Taggus

2026-12Artigo científico Acesso aberto
Ver registo simples
dc.contributor.authorCanário, Tiago Gastão Gato
dc.contributor.authorDuarte, Catarina Ribeiro
dc.contributor.authorPinheiro, Flávio L.
dc.contributor.authorPereira, João L. M.
dc.contributor.institutionNOVA Information Management School (NOVA IMS)
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School
dc.contributor.pblSpringer-Verlag Wien
dc.date.accessioned2026-03-05T10:01:02Z
dc.date.available2026-03-05T10:01:02Z
dc.date.issued2026-12
dc.descriptionCanário, T. G. G., Duarte, C. R., Pinheiro, F. L., & Pereira, J. L. M. (2026). Taggus: an automated pipeline for the extraction of characters’ social networks from portuguese fiction literature. Social Network Analysis and Mining, 16, Article 40. https://doi.org/10.1007/s13278-026-01584-6 --- FLP acknowledges the financial support provided by FCT Portugal (Fundação para a Ciência e a Tecnologia), under projects - UID/04152/2025 - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS - https://doi.org/10.54499/UID/04152/2025 (2025-01-01/2028-12-31), UID/PRR/04152/2025 https://doi.org/10.54499/UID/PRR/04152/2025 (2025-01-01/ 2026-06-30), and Know-Net-Compet (https://doi.org/10.54499/2024.07378.IACD). JLMP acknowledges the financial support from FCT Portugal within the R&D Unit Project Scope UID/00319/2025 - Centro ALGORITMI (ALGORITMI/UM).
dc.description.abstractThe Automatic identification of characters and their interactions from literary fiction is, arguably, a complex task that requires pipelines that leverage multiple Natural Language Processing (NLP) methods, such as Named Entity Recognition (NER) and Part-of-speech (POS) tagging. However, these methods are not optimized for retrieving Social Networks of Characters. Indeed, the currently available methods tend to underperform, especially in less-represented languages, due to a lack of manually annotated data for training. Here, we propose a pipeline, which we call Taggus, to extract social networks from literary fiction works in Portuguese without requiring a training phase. Our results show that compared to readily available State-of-the-Art tools—off-the-shelf NER tools and Large Language Models (ChatGPT)—the resulting pipeline, which uses POS tagging and a combination of heuristics, achieves satisfying results with an average F1-Score of 92.1% in the task of identifying characters and solving for co-reference and 74.0% in interaction detection. These represent, respectively, increases of 115.7% and 38.1% over the results achieved by the readily available State-of-the-Art tools. Further steps to improve results are outlined, including methods for detecting relationships among characters. Limitations on the size and scope of our testing samples are acknowledged and in the exclusive focus on interactions as the relationship type. The Taggus pipeline is publicly available to encourage development in this field for the Portuguese language.en
dc.description.versionpublishersversion
dc.description.versionepub_ahead_of_print
dc.format.extent15
dc.format.extent1800261
dc.identifier.doi10.1007/s13278-026-01584-6
dc.identifier.issn1869-5450
dc.identifier.otherPURE: 150830042
dc.identifier.otherPURE UUID: e66e193d-4f64-4cc8-93da-999711fe64ec
dc.identifier.otherScopus: 105030934062
dc.identifier.otherWOS: 001698971300001
dc.identifier.otherORCID: /0000-0002-0561-9641/work/207550545
dc.identifier.urihttp://hdl.handle.net/10362/200989
dc.identifier.urlhttps://www.scopus.com/pages/publications/105030934062
dc.identifier.urlhttps://www.webofscience.com/wos/woscc/full-record/WOS:001698971300001
dc.identifier.urlhttps://github.com/ticadu/taggus
dc.language.isoeng
dc.peerreviewedyes
dc.relationhttps://doi.org/10.54499/UID/04152/2025
dc.relationhttps://doi.org/10.54499/UID/PRR/04152/2025
dc.relationhttps://doi.org/10.54499/UIDB/00319/2020
dc.subjectSocial Network Analysis
dc.subjectEntity Recognition
dc.subjectEntity Extraction
dc.subjectCo-reference Resolution
dc.subjectRelationship Extraction
dc.subjectInformation Systems
dc.subjectCommunication
dc.subjectMedia Technology
dc.subjectHuman-Computer Interaction
dc.subjectComputer Science Applications
dc.titleTaggusen
dc.title.subtitlean automated pipeline for the extraction of characters’ social networks from portuguese fiction literatureen
dc.typejournal article
degois.publication.titleSocial Network Analysis and Mining
degois.publication.volume16
dspace.entity.typePublication
rcaap.rightsopenAccess

Ficheiros

Principais
A mostrar 1 - 1 de 1
Miniatura
Nome:
Taggus.pdf
Tamanho:
1.72 MB
Formato:
Adobe Portable Document Format
Ver/Abrir

Coleções

NIMS: MagIC - Artigos em revista internacional com arbitragem científica (Peer-Review articles in international journals)