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

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

6 Citations (Scopus)

3 Downloads (Pure)

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.

Original language	English
Title of host publication	Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)
Editors	Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Sara Goggi, Marko Grobelnik, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asunción Moreno, Jan Odijk, Stelios Piperidis
Place of Publication	Paris, France
Publisher	European Language Resources Association (ELRA)
Pages	4098-4104
Number of pages	7
ISBN (Print)	9782951740891
Publication status	Published - 2016
Event	International Conference on Language Resources and Evaluation (10th : 2016) - Portorož, Slovenia Duration: 23 May 2016 → 28 May 2016

Conference

Conference	International Conference on Language Resources and Evaluation (10th : 2016)
Abbreviated title	LREC 2016
Country	Slovenia
City	Portorož
Period	23/05/16 → 28/05/16

Bibliographical note

Copyright the Author(s) 2016. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

Language Change
Temporal Text Classification
Support Vector Machines
Text Categorization
Support vector machines
Language change
Temporal text classification
Text categorization

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Zampieri, M., Malmasi, S., & Dras, M. (2016). Modeling language change in historical corpora: the case of Portuguese. In N. Calzolari, K. Choukri, T. Declerck, S. Goggi, M. Grobelnik, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, ... S. Piperidis (Eds.), Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016) (pp. 4098-4104). [706] Paris, France: European Language Resources Association (ELRA).

Zampieri, Marcos ; Malmasi, Shervin ; Dras, Mark. / Modeling language change in historical corpora : the case of Portuguese. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). editor / Nicoletta Calzolari ; Khalid Choukri ; Thierry Declerck ; Sara Goggi ; Marko Grobelnik ; Bente Maegaard ; Joseph Mariani ; Hélène Mazo ; Asunción Moreno ; Jan Odijk ; Stelios Piperidis. Paris, France : European Language Resources Association (ELRA), 2016. pp. 4098-4104

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title = "Modeling language change in historical corpora: the case of Portuguese",

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.",

keywords = "Language Change, Temporal Text Classification, Support Vector Machines, Text Categorization, Support vector machines, Language change, Temporal text classification, Text categorization",

author = "Marcos Zampieri and Shervin Malmasi and Mark Dras",

note = "Copyright the Author(s) 2016. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.",

year = "2016",

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editor = "Nicoletta Calzolari and Khalid Choukri and Thierry Declerck and Sara Goggi and Marko Grobelnik and Bente Maegaard and Joseph Mariani and H{\'e}l{\`e}ne Mazo and Asunci{\'o}n Moreno and Jan Odijk and Stelios Piperidis",

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Zampieri, M, Malmasi, S & Dras, M 2016, Modeling language change in historical corpora: the case of Portuguese. in N Calzolari, K Choukri, T Declerck, S Goggi, M Grobelnik, B Maegaard, J Mariani, H Mazo, A Moreno, J Odijk & S Piperidis (eds), Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)., 706, European Language Resources Association (ELRA), Paris, France, pp. 4098-4104, International Conference on Language Resources and Evaluation (10th : 2016), Portorož, Slovenia, 23/05/16.

Modeling language change in historical corpora : the case of Portuguese. / Zampieri, Marcos; Malmasi, Shervin ; Dras, Mark.

Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). ed. / Nicoletta Calzolari; Khalid Choukri; Thierry Declerck; Sara Goggi; Marko Grobelnik; Bente Maegaard; Joseph Mariani; Hélène Mazo; Asunción Moreno; Jan Odijk; Stelios Piperidis. Paris, France : European Language Resources Association (ELRA), 2016. p. 4098-4104 706.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding contribution

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T1 - Modeling language change in historical corpora

T2 - the case of Portuguese

AU - Zampieri, Marcos

AU - Malmasi, Shervin

AU - Dras, Mark

N1 - Copyright the Author(s) 2016. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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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KW - Temporal Text Classification

KW - Support Vector Machines

KW - Text Categorization

KW - Support vector machines

KW - Language change

KW - Temporal text classification

KW - Text categorization

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SN - 9782951740891

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BT - Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016)

A2 - Calzolari, Nicoletta

A2 - Choukri, Khalid

A2 - Declerck, Thierry

A2 - Goggi, Sara

A2 - Grobelnik, Marko

A2 - Maegaard, Bente

A2 - Mariani, Joseph

A2 - Mazo, Hélène

A2 - Moreno, Asunción

A2 - Odijk, Jan

A2 - Piperidis, Stelios

PB - European Language Resources Association (ELRA)

CY - Paris, France

ER -

Zampieri M, Malmasi S , Dras M. Modeling language change in historical corpora: the case of Portuguese. In Calzolari N, Choukri K, Declerck T, Goggi S, Grobelnik M, Maegaard B, Mariani J, Mazo H, Moreno A, Odijk J, Piperidis S, editors, Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016). Paris, France: European Language Resources Association (ELRA). 2016. p. 4098-4104. 706