Author profiling with doc2vec neural network-based document embeddings

Ilia Markov; Helena Gómez-Adorno; Juan Pablo Posadas-Durán; Grigori Sidorov; Alexander Gelbukh

doi:10.1007/978-3-319-62428-0_9

Author profiling with doc2vec neural network-based document embeddings

Ilia Markov, Helena Gómez-Adorno, Juan Pablo Posadas-Durán, Grigori Sidorov, Alexander Gelbukh

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

34 Citas (Scopus)

Resumen

To determine author demographics of texts in social media such as Twitter, blogs, and reviews, we use doc2vec document embeddings to train a logistic regression classifier. We experimented with age and gender identification on the PAN author profiling 2014–2016 corpora under both single- and cross-genre conditions. We show that under certain settings the neural network-based features outperform the traditional features when using the same classifier. Our method outperforms existing state of the art under some settings, though the current state-of-the-art results on those tasks have been quite weak.

Idioma original	Inglés
Título de la publicación alojada	Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings
Editores	Obdulia Pichardo-Lagunas, Sabino Miranda-Jimenez
Editorial	Springer Verlag
Páginas	117-131
Número de páginas	15
ISBN (versión impresa)	9783319624273
DOI	https://doi.org/10.1007/978-3-319-62428-0_9
Estado	Publicada - 2017
Evento	15th Mexican International Conference on Artificial Intelligence, MICAI 2016 - Cancun, México Duración: 23 oct. 2016 → 28 oct. 2016

Serie de la publicación

Nombre	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen	10062 LNAI
ISSN (versión impresa)	0302-9743
ISSN (versión digital)	1611-3349

Conferencia

Conferencia	15th Mexican International Conference on Artificial Intelligence, MICAI 2016
País/Territorio	México
Ciudad	Cancun
Período	23/10/16 → 28/10/16

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10.1007/978-3-319-62428-0_9

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Markov, I., Gómez-Adorno, H., Posadas-Durán, J. P., Sidorov, G., & Gelbukh, A. (2017). Author profiling with doc2vec neural network-based document embeddings. En O. Pichardo-Lagunas, & S. Miranda-Jimenez (Eds.), Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings (pp. 117-131). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10062 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-319-62428-0_9

Markov, Ilia ; Gómez-Adorno, Helena ; Posadas-Durán, Juan Pablo et al. / Author profiling with doc2vec neural network-based document embeddings. Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings. editor / Obdulia Pichardo-Lagunas ; Sabino Miranda-Jimenez. Springer Verlag, 2017. pp. 117-131 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Author profiling with doc2vec neural network-based document embeddings",

abstract = "To determine author demographics of texts in social media such as Twitter, blogs, and reviews, we use doc2vec document embeddings to train a logistic regression classifier. We experimented with age and gender identification on the PAN author profiling 2014–2016 corpora under both single- and cross-genre conditions. We show that under certain settings the neural network-based features outperform the traditional features when using the same classifier. Our method outperforms existing state of the art under some settings, though the current state-of-the-art results on those tasks have been quite weak.",

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Markov, I, Gómez-Adorno, H, Posadas-Durán, JP , Sidorov, G & Gelbukh, A 2017, Author profiling with doc2vec neural network-based document embeddings. En O Pichardo-Lagunas & S Miranda-Jimenez (eds.), Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 10062 LNAI, Springer Verlag, pp. 117-131, 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancun, México, 23/10/16. https://doi.org/10.1007/978-3-319-62428-0_9

Author profiling with doc2vec neural network-based document embeddings. / Markov, Ilia; Gómez-Adorno, Helena; Posadas-Durán, Juan Pablo et al.
Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings. ed. / Obdulia Pichardo-Lagunas; Sabino Miranda-Jimenez. Springer Verlag, 2017. p. 117-131 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10062 LNAI).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Author profiling with doc2vec neural network-based document embeddings

AU - Markov, Ilia

AU - Gómez-Adorno, Helena

AU - Posadas-Durán, Juan Pablo

AU - Sidorov, Grigori

AU - Gelbukh, Alexander

N1 - Publisher Copyright: © Springer International Publishing AG 2017.

PY - 2017

Y1 - 2017

N2 - To determine author demographics of texts in social media such as Twitter, blogs, and reviews, we use doc2vec document embeddings to train a logistic regression classifier. We experimented with age and gender identification on the PAN author profiling 2014–2016 corpora under both single- and cross-genre conditions. We show that under certain settings the neural network-based features outperform the traditional features when using the same classifier. Our method outperforms existing state of the art under some settings, though the current state-of-the-art results on those tasks have been quite weak.

AB - To determine author demographics of texts in social media such as Twitter, blogs, and reviews, we use doc2vec document embeddings to train a logistic regression classifier. We experimented with age and gender identification on the PAN author profiling 2014–2016 corpora under both single- and cross-genre conditions. We show that under certain settings the neural network-based features outperform the traditional features when using the same classifier. Our method outperforms existing state of the art under some settings, though the current state-of-the-art results on those tasks have been quite weak.

KW - Author profiling

KW - Document embeddings

KW - Machine learning

KW - Neural networks

KW - doc2vec

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DO - 10.1007/978-3-319-62428-0_9

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SN - 9783319624273

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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EP - 131

BT - Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings

A2 - Pichardo-Lagunas, Obdulia

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T2 - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016

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ER -

Markov I, Gómez-Adorno H, Posadas-Durán JP , Sidorov G , Gelbukh A. Author profiling with doc2vec neural network-based document embeddings. En Pichardo-Lagunas O, Miranda-Jimenez S, editores, Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings. Springer Verlag. 2017. p. 117-131. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-62428-0_9

Author profiling with doc2vec neural network-based document embeddings

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