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Detecting early signs of depression in the conversational domain: The role of transfer learning in low-resource scenarios ...
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Predicting subjective well-being in a high-risk sample of Russian mental health app users
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In: EPJ Data Sci (2022)
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LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis
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In: https://hal.archives-ouvertes.fr/hal-03294371 ; 2021 (2021)
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UPV at CheckThat! 2021: Mitigating Cultural Differences for Identifying Multilingual Check-worthy Claims ...
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Categorizing Misogynistic Behaviours in Italian, English and Spanish Tweets ; Categorización de comportamientos misóginos en tweets en italiano, inglés y español
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Masking and BERT-based Models for Stereotype Identification ; Modelos Basados en Enmascaramiento y en BERT para la Identificación de Estereotipos
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The impact of emotional signals on credibility assessment
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In: J Assoc Inf Sci Technol (2021)
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Abstract:
Fake news is considered one of the main threats of our society. The aim of fake news is usually to confuse readers and trigger intense emotions to them in an attempt to be spread through social networks. Even though recent studies have explored the effectiveness of different linguistic patterns for fake news detection, the role of emotional signals has not yet been explored. In this paper, we focus on extracting emotional signals from claims and evaluating their effectiveness on credibility assessment. First, we explore different methodologies for extracting the emotional signals that can be triggered to the users when they read a claim. Then, we present emoCred, a model that is based on a long‐short term memory model that incorporates emotional signals extracted from the text of the claims to differentiate between credible and non‐credible ones. In addition, we perform an analysis to understand which emotional signals and which terms are the most useful for the different credibility classes. We conduct extensive experiments and a thorough analysis on real‐world datasets. Our results indicate the importance of incorporating emotional signals in the credibility assessment problem.
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Keyword:
Research Articles
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URL: https://doi.org/10.1002/asi.24480 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8453501/ http://www.ncbi.nlm.nih.gov/pubmed/34589557
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On the Detection of False Information: From Rumors to Fake News
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Dependency Syntax in the Automatic Detection of Irony and Stance
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Multilingual Irony Detection with Dependency Syntax and Neural Models
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In: Proceedings of the 28th International Conference on Computational Linguistics ; 28th International Conference on Computational Linguistics (COLING 2020) ; https://hal.archives-ouvertes.fr/hal-03102480 ; 28th International Conference on Computational Linguistics (COLING 2020), Dec 2020, Barcelona (Online), Spain. pp.1346-1358 ; https://www.aclweb.org/anthology/2020.coling-main.116/ (2020)
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Irony Detection in a Multilingual Context
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In: ECIR ; https://hal.archives-ouvertes.fr/hal-02889008 ; ECIR, Apr 2020, online, Portugal (2020)
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LIMSI_UPV at SemEval-2020 Task 9: Recurrent Convolutional Neural Network for Code-mixed Sentiment Analysis ...
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Classifier Combination Approach for Question Classification for Bengali Question Answering System ...
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Multilingual Irony Detection with Dependency Syntax and Neural Models ...
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Multilingual Irony Detection with Dependency Syntax and Neural Models ...
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The Role of Personality and Linguistic Patterns in Discriminating Between Fake News Spreaders and Fact Checkers
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In: Natural Language Processing and Information Systems (2020)
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Do Linguistic Features Help Deep Learning? The Case of Aggressiveness in Mexican Tweets
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