Un enfoque del filtrado de léxico para perfiles de autor

• Autores: Jenny Alexandra Ortiz Zambrano, Arturo Montejo Ráez , César Espin Riofrio
• Localización: Procesamiento del lenguaje natural, ISSN 1135-5948, Nº. 71, 2023, págs. 75-86
• Idioma: varios idiomas
• Títulos paralelos:
  • An approach to lexicon filtering for author profiling
• Enlaces
  • Texto completo
• Resumen
  • Multiple

    Este trabajo estudia la influencia de un léxico general del español y un léxico específico del dominio en un problema de clasificación de textos. En concreto, abordamos el impacto de la elección de léxicos para el modelado de usuarios. Para ello, identificamos el género y la profesión como rasgos demográficos, y la ideología política como rasgo psicográfico a partir de un conjunto de tuits. Experimentamos con métodos de aprendizaje automático y aprendizaje supervisado para crear un modelo de predicción con el que evaluamos nuestro léxico específico. Nuestros resultados muestran que la elección y/o construcción de léxicos para apoyar la resolución de esta tarea puede seguir una estrategia determinada, caracterizada por el dominio del léxico y el tipo de palabras que contiene.

  • English

    This paper studies the influence of a general Spanish lexicon and a domain-specific lexicon on a text classification problem. Specifically, we address the impact of the choice of lexicons for user modelling. To do so, we identify gender and profession as demographic traits, and political ideology as a psychographic trait from a set of tweets. We experimented with machine learning and supervised learning methods to create a prediction model with which we evaluated our specific lexicon. Our results show that the choice and/or construction of lexicons to support the resolution of this task can follow a given strategy, characterised by the domain of the lexicon and the type of words it contains.

• Referencias bibliográficas
  • Campillos-Llanos, L., A. Valverde-Mateos, A. Capllonch-Carrión, and A. Moreno- Sandoval. 2021. A clinical trials corpus annotated with umls...
  • Canete, J., G. Chaperon, R. Fuentes, et al. 2020. Spanish pre-trained bert model and evaluation data. Pml4dc at iclr, 2020:1– 10.
  • Carrasco, S. S. and R. C. Rosillo. 2022. Loscalis at politices 2022: Political author profiling using beto and maria. In Proceedings of the...
  • Clark, E. V. 1995. The lexicon in acquisition. Number 65. Cambridge University Press. Conneau, A., K. Khandelwal, N. Goyal, V. Chaudhary,...
  • Davidson, T., D. Warmsley, M. Macy, and I. Weber. 2017. Automated hate speech detection and the problem of offensive language. In Proceedings...
  • Devlin, J., M.-W. Chang, K. Lee, and K. Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding....
  • Eder, M., J. Rybicki, and M. Kestemont. 2016. Stylometry with r: a package for computational text analysis. The R Journal, 8(1).
  • Erikson, R. S. and K. L. Tedin. 2015. American public opinion: Its origins, content and impact. Routledge.
  • Espin-Riofrio, C., J. Ortiz-Zambrano, and A. Montejo-Ráez. 2022. Sinai at politices 2022: Exploring relative frequency of words in stylometrics...
  • García-Díaz, J. A., á. Almela, G. Alcaraz- Mármol, and R. Valencia-García. 2020. Umucorpusclassifier: Compilation and evaluation of linguistic...
  • García-Díaz, J. A., R. Colomo-Palacios, and R. Valencia-García. 2022. Psychographic traits identification based on political ideology: An...
  • García-Díaz, J. A., S. M. Jiménez-Zafra, M.-T. M. Valdivia, F. García-Sánchez, L. A. Ureria-López, and R. Valencia- García. 2022. Overview...
  • Gutiérrez Fandiño, A., J. Armengol Estapé, et al. 2022. Maria: Spanish language models. Procesamiento del Lenguaje Natural, 68.
  • Holmes, D. I. 1994. Authorship attribution. Computers and the Humanities, 28(2):87– 106.
  • Hoover, D. L. 2007. Corpus stylistics, stylometry, and the styles of henry james. Style, 41(2):174–203.
  • Hu, M. and B. Liu. 2004. Mining and summarizing customer reviews. In Proceedings of the tenth ACM SIGKDD international conference on Knowledge...
  • Ikae, C., S. Nath, and J. Savoy. 2019. Unine at pan-clef 2019: Bots and gender task. In CLEF (Working Notes).
  • Juola, P. et al. 2008. Authorship attribution. Foundations and Trends® in Information Retrieval, 1(3):233–334.
  • Lanza, C., A. Folino, E. Pasceri, and A. Perri. 2021. Lexicon of pandemics: A semantic analysis of the spanish flu and the covid-19 timeframe...
  • McClelland, J. L. and D. E. Rumelhart. 1981. An interactive activation model of context effects in letter perception: I. an account of basic...
  • Mohammad, S. M. 2017. Word affect intensities. arXiv preprint arXiv:1704.08798.
  • Molina-González, M. D., E. Martínez- Cámara, M. T. Martín-Valdivia, and L. A. Urena-López. 2014. Cross-domain sentiment analysis using spanish...
  • Molina-González, M. D., E. Martínez- Cámara, M.-T. Martín-Valdivia, and J. M. Perea-Ortega. 2013. Semantic orientation for polarity classification...
  • Moreira, G. L. 2021. El léxico del turismo en los diccionarios de español (the tourism lexicon in spanish dictionaries). Termin`alia,...
  • Moreno-Ortiz, A. and C. P. Hernández. 2013. Lexicon-based sentiment analysis of twitter messages in spanish. Procesamiento del lenguaje natural,...
  • Mosquera, A. 2022. Alejandro mosquera at politices 2022: Towards robust spanish author profiling and lessons learned from adversarial attacks....
  • Neal, T., K. Sundararajan, A. Fatima, Y. Yan, Y. Xiang, and D. Woodard. 2017. Surveying stylometry techniques and applications. ACM Computing...
  • Ortiz-Zambrano, J., C. Espin-Riofrio, and A. Montejo-Ráez. 2022. Transformers for lexical complexity prediction in spanish language. Procesamiento...
  • Plaza-del Arco, F. M., M. D. Molina- González, S. M. Jiménez-Zafra, and M. T. Martín-Valdivia. 2018. Lexicon adaptation for spanish emotion...
  • Plaza-del Arco, F. M., A. Montejo-Ráez, L. A. Urena-López, and M. Martín- Valdivia. 2021. Offendes: A new corpus in spanish for offensive...
  • Roy, G. and S. Sharma. 2021. Analyzing one-day tour trends during covid-19 disruption–applying push and pull theory and text mining approach....
  • Sánchez-Junquera, J., S. P. Ponzetto, and P. Rosso. 2020. A twitter political corpus of the 2019 10n spanish election. In International Conference...
  • Sandoval, L. G. M., A. P. Quimbaya, C. E. C. Gutiérrez, J. F. G. Pachón, and D. F. V. Ramírez. 2022. Comparación de métodos de análisis de...
  • Savoy, J. 2020. Machine learning methods for stylometry. Springer.
  • Sidorov, G., S. Miranda-Jiménez, F. Viveros- Jiménez, A. Gelbukh, N. Castro-Sánchez, F. Velásquez, I. Díaz-Rangel, S. Suárez- Guerra, A. Trevino,...
  • Taboada, M. 2017. SFU Review Corpus — Maite Taboada.
  • Taboada, M., J. Brooke, M. Tofiloski, K. Voll, and M. Stede. 2011. Lexiconbased methods for sentiment analysis. Computational linguistics,...
  • Tweedie, F. J., S. Singh, and D. I. Holmes. 1996. Neural network applications in stylometry: The federalist papers. Computers and the Humanities,...
  • Vaswani, A., N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin. 2017. Attention is all you need. Advances...
  • Villa-Cueva, E., I. González-Franco, F. Sanchez-Vega, and A. P. López- Monroy. 2022. Nlp-cimat at politices 2022: Politibeto, a domain-adapted...
  • Vossen, P. 1998. A multilingual database with lexical semantic networks. Dordrecht: Kluwer Academic Publishers. doi, 10:978–94.
  • Webb, S. 2021. The lemma dilemma: How should words be operationalized in research and pedagogy? Studies in Second Language Acquisition, 43(5):941–949.
  • Zhang, M., Y. Liu, H. Luan, and M. Sun. 2017. Adversarial training for unsupervised bilingual lexicon induction. In Proceedings of the 55th...