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Dependency Syntax in the Automatic Detection of Irony and Stance ; Sintaxis de dependencias en la detección automática de ironía y posicionamiento
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Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning
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A Methodology for the Automatic Annotation of Factuality in Spanish ; Una metodología para la anotación automática de la factualidad en español
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Generación de textos en ruso mediante técnicas de Aprendizaje Automático para la industria del lenguaje
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Some Contributions to Interactive Machine Translation and to the Applications of Machine Translation for Historical Documents
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A BDI Empathic Agent Model Based on a Multidimensional Cross-Cultural Emotion Representation
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Diseño y desarrollo de un juego de navegador para comenzar a aprender construcciones básicas de programación
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Escansión automática de poesía española sin silabación ; Automatic Scansion of Spanish Poetry without Syllabification
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Architecture design of a reinforcement environment for learning sign languages
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Arquitectura de componentes de refuerzo del aprendizaje de lengua de señas empleando proximidad fonológica
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Classifying Spanish se constructions: from bag of words to language models ; Clasificación de construcciones con se en español: de modelos de bolsa de palabras a modelos de lenguaje
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GPLSI team at CheckThat! 2021: Fine-tuning BETO and RoBERTa
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NECOS: An annotated corpus to identify constructive news comments in Spanish ; NECOS: Un corpus anotado para identificar comentarios constructivos de noticias en español
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Impact of Text Length for Information Retrieval Tasks based on Probabilistic Topics ; Influencia de la Longitud del Texto en Tareas de Recuperación de Información mediante Tópicos Probabilísticos
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HeadlineStanceChecker: Exploiting summarization to detect headline disinformation
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Abstract:
The headline of a news article is designed to succinctly summarize its content, providing the reader with a clear understanding of the news item. Unfortunately, in the post-truth era, headlines are more focused on attracting the reader’s attention for ideological or commercial reasons, thus leading to mis- or disinformation through false or distorted headlines. One way of combating this, although a challenging task, is by determining the relation between the headline and the body text to establish the stance. Hence, to contribute to the detection of mis- and disinformation, this paper proposes an approach—HeadlineStanceChecker—that determines the stance of a headline with respect to the body text to which it is associated. The novelty rests on the use of a two-stage classification architecture that uses summarization techniques to shape the input for both classifiers instead of directly passing the full news body text, thereby reducing the amount of information to be processed while keeping important information. Specifically, summarization is done through Positional Language Models leveraging on semantic resources to identify salient information in the body text that is then compared to its corresponding headline. The results obtained show that our approach achieves 94.31% accuracy for the overall classification and the best FNC-1 relative score compared with the state of the art. It is especially remarkable that the system, which uses only the relevant information provided by the automatic summaries instead of the whole text, is able to classify the different stance categories with very competitive results, especially in the discuss stance between the headline and the news body text. It can be concluded that using automatic extractive summaries as input of our approach together with the two-stage architecture is an appropriate solution to the problem. ; This research work has been partially funded by Generalitat Valenciana through project “SIIA: Tecnologías del lenguaje humano para una sociedad inclusiva, igualitaria, y accesible” with grant reference PROMETEU/2018/089, by the Spanish Government through project RTI2018-094653-B-C22: “Modelang: Modeling the behavior of digital entities by Human Language Technologies”, as well as by the project RTI2018-094649-B-I00: “INTEGER - Intelligent Text Generation”. Also, this paper is also based upon work from COST Action CA18231 “Multi3Generation: Multi-task, Multilingual, Multi-modal Language Generation”.
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Keyword:
Applied computing; Document management and text processing; Fake news; Lenguajes y Sistemas Informáticos; Misleading headlines; Natural Language Processing; Semantic summarization; Stance detection
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URL: https://doi.org/10.1016/j.websem.2021.100660
http://hdl.handle.net/10045/118249
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Bertinho: Galician BERT Representations ; Bertinho: Representaciones BERT para el gallego
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Consumer Cynicism Identification for Spanish Reviews using a Spanish Transformer Model ; Identificación del cinismo del consumidor para reseñas en español utilizando un modelo de transformador español
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Buscando robustez en un mundo multilingüe: de pipelines a embeddings ; Seeking robustness in a multilingual world: from pipelines to embeddings
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Doval, Yerai. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2021
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A benchmark of Spanish language datasets for computationally driven research
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