Author profiling with doc2vec neural network-based document embeddings

I. Markov; H. Gómez-Adorno; J.-P. Posadas-Durán; G. Sidorov; A. Gelbukh

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

Author profiling with doc2vec neural network-based document embeddings

I. Markov
, H. Gómez-Adorno
, J.-P. Posadas-Durán
, G. Sidorov
, A. Gelbukh

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

Abstract

© Springer International Publishing AG 2017.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.

Original language	English
Title of host publication	Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings
Editors	O. Pichardo-Lagunas, S. Miranda-Jimenez
Publisher	Springer Verlag
Pages	117-131
ISBN (Print)	9783319624273
DOIs	https://doi.org/10.1007/978-3-319-62428-0_9
Publication status	Published - 2017
Externally published	Yes
Event	15th Mexican International Conference on Artificial Intelligence, MICAI 2016 - Cancun, Mexico Duration: 23 Oct 2016 → 28 Oct 2016

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	15th Mexican International Conference on Artificial Intelligence, MICAI 2016
Country/Territory	Mexico
City	Cancun
Period	23/10/16 → 28/10/16

Funding

Acknowledgments. This work was partially supported by the Mexican Government (CONACYT projects 240844 and 20161958, SNI, COFAA-IPN, SIP-IPN 20151406, 20161947, 20161958, 20151589, 20162204, and 20162064).

Funders	Funder number
Mexican Government
Consejo Nacional de Ciencia y Tecnología	20161958, 240844
Sistema Nacional de Investigadores	SIP-IPN 20151406, 20151589, 20162204, 20162064, 20161947

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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. In 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)). Springer Verlag. https://doi.org/10.1007/978-3-319-62428-0_9

Markov, I. ; Gómez-Adorno, H. ; Posadas-Durán, J.-P. 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 / O. Pichardo-Lagunas ; S. 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)).

@inproceedings{126617ef53fa4ec4a0c0bbd348952134,

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

abstract = "{\textcopyright} Springer International Publishing AG 2017.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.",

author = "I. Markov and H. G{\'o}mez-Adorno and J.-P. Posadas-Dur{\'a}n and G. Sidorov and A. Gelbukh",

year = "2017",

doi = "10.1007/978-3-319-62428-0\_9",

language = "English",

isbn = "9783319624273",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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editor = "O. Pichardo-Lagunas and S. Miranda-Jimenez",

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

note = "15th Mexican International Conference on Artificial Intelligence, MICAI 2016 ; Conference date: 23-10-2016 Through 28-10-2016",

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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. in 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), Springer Verlag, pp. 117-131, 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Cancun, Mexico, 23/10/16. https://doi.org/10.1007/978-3-319-62428-0_9

Author profiling with doc2vec neural network-based document embeddings. / Markov, I.; Gómez-Adorno, H.; Posadas-Durán, J.-P. et al.
Advances in Soft Computing - 15th Mexican International Conference on Artificial Intelligence, MICAI 2016, Proceedings. ed. / O. Pichardo-Lagunas; S. 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)).

Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

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

AU - Markov, I.

AU - Gómez-Adorno, H.

AU - Posadas-Durán, J.-P.

AU - Sidorov, G.

AU - Gelbukh, A.

PY - 2017

Y1 - 2017

N2 - © Springer International Publishing AG 2017.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 - © Springer International Publishing AG 2017.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.

U2 - 10.1007/978-3-319-62428-0_9

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

M3 - Conference contribution

SN - 9783319624273

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

SP - 117

EP - 131

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

A2 - Pichardo-Lagunas, O.

A2 - Miranda-Jimenez, S.

PB - Springer Verlag

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

Y2 - 23 October 2016 through 28 October 2016

ER -

Markov I, Gómez-Adorno H, Posadas-Durán JP, Sidorov G, Gelbukh A. Author profiling with doc2vec neural network-based document embeddings. In Pichardo-Lagunas O, Miranda-Jimenez S, editors, 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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