Modeling Language Change in Historical Corpora: The Case of Portuguese

Marcos Zampieri; Shervin Malmasi; Mark Dras

Modeling Language Change in Historical Corpora: The Case of Portuguese

Marcos Zampieri, Shervin Malmasi, Mark Dras

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Abstract

This paper presents a number of experiments to model changes in a historical Portuguese corpus composed of literary texts for the purpose of temporal text classification. Algorithms were trained to classify texts with respect to their publication date taking into account lexical variation represented as word n-grams, and morphosyntactic variation represented by part-of-speech (POS) distribution. We report results of 99.8% accuracy using word unigram features with a Support Vector Machines classifier to predict the publication date of documents in time intervals of both one century and half a century. A feature analysis is performed to investigate the most informative features for this task and how they are linked to language change.

Anthology ID:: L16-1647
Volume:: Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)
Month:: May
Year:: 2016
Address:: Portorož, Slovenia
Editors:: Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:: LREC
SIG:
Publisher:: European Language Resources Association (ELRA)
Note:
Pages:: 4098–4104
Language:
URL:: https://aclanthology.org/L16-1647/
DOI:
Bibkey:
Cite (ACL):: Marcos Zampieri, Shervin Malmasi, and Mark Dras. 2016. Modeling Language Change in Historical Corpora: The Case of Portuguese. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 4098–4104, Portorož, Slovenia. European Language Resources Association (ELRA).
Cite (Informal):: Modeling Language Change in Historical Corpora: The Case of Portuguese (Zampieri et al., LREC 2016)
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PDF:: https://aclanthology.org/L16-1647.pdf

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@inproceedings{zampieri-etal-2016-modeling,
    title = "Modeling Language Change in Historical Corpora: The Case of {P}ortuguese",
    author = "Zampieri, Marcos  and
      Malmasi, Shervin  and
      Dras, Mark",
    editor = "Calzolari, Nicoletta  and
      Choukri, Khalid  and
      Declerck, Thierry  and
      Goggi, Sara  and
      Grobelnik, Marko  and
      Maegaard, Bente  and
      Mariani, Joseph  and
      Mazo, Helene  and
      Moreno, Asuncion  and
      Odijk, Jan  and
      Piperidis, Stelios",
    booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
    month = may,
    year = "2016",
    address = "Portoro{\v{z}}, Slovenia",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://aclanthology.org/L16-1647/",
    pages = "4098--4104",
    abstract = "This paper presents a number of experiments to model changes in a historical Portuguese corpus composed of literary texts for the purpose of temporal text classification. Algorithms were trained to classify texts with respect to their publication date taking into account lexical variation represented as word n-grams, and morphosyntactic variation represented by part-of-speech (POS) distribution. We report results of 99.8{\%} accuracy using word unigram features with a Support Vector Machines classifier to predict the publication date of documents in time intervals of both one century and half a century. A feature analysis is performed to investigate the most informative features for this task and how they are linked to language change."
}

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%0 Conference Proceedings
%T Modeling Language Change in Historical Corpora: The Case of Portuguese
%A Zampieri, Marcos
%A Malmasi, Shervin
%A Dras, Mark
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Grobelnik, Marko
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Helene
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16)
%D 2016
%8 May
%I European Language Resources Association (ELRA)
%C Portorož, Slovenia
%F zampieri-etal-2016-modeling
%X This paper presents a number of experiments to model changes in a historical Portuguese corpus composed of literary texts for the purpose of temporal text classification. Algorithms were trained to classify texts with respect to their publication date taking into account lexical variation represented as word n-grams, and morphosyntactic variation represented by part-of-speech (POS) distribution. We report results of 99.8% accuracy using word unigram features with a Support Vector Machines classifier to predict the publication date of documents in time intervals of both one century and half a century. A feature analysis is performed to investigate the most informative features for this task and how they are linked to language change.
%U https://aclanthology.org/L16-1647/
%P 4098-4104

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Markdown (Informal)

[Modeling Language Change in Historical Corpora: The Case of Portuguese](https://aclanthology.org/L16-1647/) (Zampieri et al., LREC 2016)

Modeling Language Change in Historical Corpora: The Case of Portuguese (Zampieri et al., LREC 2016)

ACL

Marcos Zampieri, Shervin Malmasi, and Mark Dras. 2016. Modeling Language Change in Historical Corpora: The Case of Portuguese. In Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16), pages 4098–4104, Portorož, Slovenia. European Language Resources Association (ELRA).