Abstract
Language variety identification is an author profiling subtask which aims to detect lexical and semantic variations in order to classify different varieties of the same language. In this work we focus on the use of distributed representations of words and documents using the continuous Skip-gram model. We compare this model with three recent approaches: Information Gain Word-Patterns, TF-IDF graphs and Emotion-labeled Graphs, in addition to several baselines. We evaluate the models introducing the Hispablogs dataset, a new collection of Spanish blogs from five different countries: Argentina, Chile, Mexico, Peru and Spain. Experimental results show state-of-the-art performance in language variety identification. In addition, our empirical analysis provides interesting insights on the use of the evaluated approaches.
This research has been carried out within the framework of the European Commission WIQ-EI IRSES (no. 269180) and DIANA - Finding Hidden Knowledge in Texts (TIN2012-38603-C02) projects. The work of the second author was partially funded by Autoritas Consulting SA and by Spanish the Ministry of Economics by means of a ECOPORTUNITY IPT-2012-1220-430000 grant. We would like to thank Tomas Mikolov for his support and comments about distributed representations.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Barto, A.G.: Reinforcement learning: An introduction. MIT press (1998)
Bengio, Y., Ducharme, R., Vincent, P., Janvin, C.: A neural probabilistic language model. The Journal of Machine Learning Research 3, 1137–1155 (2003)
Dumais, S.T.: Latent semantic analysis. Annual Review of Information Science and Technology 38(1), 188–230 (2004)
Gutmann, M.U., Hyvärinen, A.: Noise-contrastive estimation of unnormalized statistical models, with applications to natural image statistics. The Journal of Machine Learning Research 13(1), 307–361 (2012)
Hinton, G.E., McClelland, J.L., Rumelhart, D.E.: Distributed representations. In: Rumelhart, D.E., McClelland, J.L., (eds.) Parallel Distributed Processing: Explorations in the Microstructure of Cognition. MIT Press (1986)
Kim, Y.: Convolutional neural networks for sentence classification. In: Proceedings of the International Conference on Empirical Methods in Natural Language Processing (2014)
Le, Q.V., Mikolov, T.: Distributed representations of sentences and documents. In: Proceedings of the 31st International Conference on Machine Learning (2014)
Levin, B.: English verb classes and alternations. University of Chicago Press, Chicago (1993)
Maier, W., Gómez-Rodríguez, C.: Language variety identification in Spanish tweets. In: Proceedings of the EMNLP’2014 Workshop on Language Technology for Closely Related Languages and Language Variants, pp. 25–35. Association for Computational Linguistics, Doha, Qatar, October 2014. http://emnlp2014.org/workshops/LT4CloseLang/call.html
Martí, M.A., Bertran, M., Taulé, M., Salamó, M.: Distributional approach based on syntactic dependencies for discovering constructions. Computational Linguistics (2015, under review)
Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. In: Proceedings of Workshop at International Conference on Learning Representations (2013)
Mikolov, T., Karafiát, M., Burget, L., Cernockỳ, J., Khudanpur, S.: Recurrent neural network based language model. In: INTERSPEECH 2010, 11th Annual Conference of the International Speech Communication Association, Makuhari, Chiba, Japan, pp. 1045–1048, September 26–30, 2010
Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Advances in Neural Information Processing Systems, vol. 26, pp. 3111–3119 (2013)
Mnih, A., Teh, Y.W.: A fast and simple algorithm for training neural probabilistic language models. arXiv preprint arXiv:1206.6426 (2012)
Mohammad, S.M., Yang, T.: Tracking sentiment in mail: how gender differ on emotional axes. In: Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (2011)
Morin, F., Bengio, Y.: Hierarchical probabilistic neural network language model. In: Proceedings of the International Workshop on Artificial Intelligence and Statistics, pp. 246–252. Citeseer (2005)
Pennebaker, J.W.: The secret life of pronouns: What our words say about us. Bloomsbury Press (2011)
Rangel, F., Rosso, P.: On the impact of emotions on author profiling. Information Processing & Management, Special Issue on Emotion and Sentiment in Social and Expressive Media (2015, in press)
Rangel, F., Rosso, P., Chugur, I., Potthast, M., Trenkmann, M., Stein, B., Verhoeven, B., Daelemans, W.: Overview of the 2nd author profiling task at pan 2014. In: Cappellato, L., Ferro, N., Halvey, M., Kraaij, W. (eds.) CLEF 2014 Labs and Workshops, Notebook Papers. CEUR-WS.org, vol. 1180 (2014)
Rangel, F., Rosso, P., Koppel, M., Stamatatos, E., Inches, G.: Overview of the author profiling task at pan 2013. In: Forner P., Navigli R., Tufis, D. (eds.) Notebook Papers of CLEF 2013 LABs and Workshops. CEUR-WS.org, vol. 1179 (2013)
Sadat, F., Kazemi, F., Farzindar, A.: Automatic identification of arabic language varieties and dialects in social media. In: Proceeding of the 1st International Workshop on Social Media Retrieval and Analysis SoMeRa (2014)
Salton, G., Wong, A., Yang, C.S.: A vector space model for automatic indexing. Communications of the ACM 18(11), 613–620 (1975)
Sidorov, G., Miranda-Jimnez, S., Viveros-Jimnez, F., Gelbukh, F., Castro-Snchez, N., Velsquez, F., Daz-Rangel, I., Surez-Guerra, S., Trevio, A., Gordon-Miranda, J.: Empirical study of opinion mining in spanish tweets. In: 11th Mexican International Conference on Artificial Intelligence, MICAI, pp. 1–4 (2012)
Zampieri, M., Gebrekidan-Gebre, B.: Automatic identification of language varieties: the case of portuguese. In: Proceedings of the Conference on Natural Language Processing (2012)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Franco-Salvador, M., Rangel, F., Rosso, P., Taulé, M., Antònia Martít, M. (2015). Language Variety Identification Using Distributed Representations of Words and Documents. In: Mothe, J., et al. Experimental IR Meets Multilinguality, Multimodality, and Interaction. CLEF 2015. Lecture Notes in Computer Science(), vol 9283. Springer, Cham. https://doi.org/10.1007/978-3-319-24027-5_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-24027-5_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-24026-8
Online ISBN: 978-3-319-24027-5
eBook Packages: Computer ScienceComputer Science (R0)