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Mental Disorders on Online Social Media Through the Lens of Language and Behaviour: Analysis and Visualisation ...
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Text mining for online mental health state and personality assessment
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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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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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The Role of Personality and Linguistic Patterns in Discriminating Between Fake News Spreaders and Fact Checkers
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Abstract:
[EN] Users play a critical role in the creation and propagation of fake news online by consuming and sharing articles with inaccurate information either intentionally or unintentionally. Fake news are written in a way to confuse readers and therefore understanding which articles contain fabricated information is very challenging for non-experts. Given the di culty of the task, several fact checking websites have been developed to raise awareness about which articles contain fabricated information. As a result of those platforms, several users are interested to share posts that cite evidence with the aim to refute fake news and warn other users. These users are known as fact checkers. However, there are users who tend to share false information, who can be characterised as potential fake news spreaders. In this paper, we propose the CheckerOrSpreader model that can classify a user as a potential fact checker or a potential fake news spreader. Our model is based on a Convolutional Neural Network (CNN) and combines word embeddings with features that represent users' personality traits and linguistic patterns used in their tweets. Experimental results show that leveraging linguistic patterns and personality traits can improve the performance in di erentiating between checkers and spreaders. ; The work of the first author is supported by the SNSF Early Postdoc Mobility grant under the project Early Fake News Detection on Social Media, Switzerland (P2TIP2 181441). The work of Paolo Rosso is partially funded by the Spanish MICINN under the research project MISMIS-FAKEnHATE on Misinformation and Miscommunication in social media: FAKE news and HATE speech (PGC2018- 096212-B-C31). ; Giachanou, A.; Ríssola, EA.; Ghanem, B.; Crestani, F.; Rosso, P. (2020). The Role of Personality and Linguistic Patterns in Discriminating Between Fake News Spreaders and Fact Checkers. Springer. 181-192. https://doi.org/10.1007/978-3-030-51310-8_17 ; S ; 181 ; 192 ; Bai, S., Zhu, T., Cheng, L.: Big-Five Personality Prediction Based on User Behaviors at Social Network Sites. https://arxiv.org/abs/1204.4809 (2012) ; Bastos, M.T., Mercea, D.: The Brexit botnet and user-generated hyperpartisan news. Soc. Sci. Comput. Rev. 37(1), 38–54 (2019) ; Burbach, L., Halbach, P., Ziefle, M., Calero Valdez, A.: Who shares fake news in online social networks? In: Proceedings of the 27th ACM Conference on User Modeling, Adaptation and Personalization, UMAP 2019, pp. 234–242 (2019) ; Cer, D., et al.: Universal Sentence Encoder. https://arxiv.org/abs/1803.11175 (2018) ; DiFranzo, D., Gloria, M.J.K.: Filter Bubbles and Fake News. ACM Crossroads 23(3), 32–35 (2017) ; Farías, D.I.H., Patti, V., Rosso, P.: Irony detection in Twitter: the role of affective content. ACM Trans. Internet Technol. (TOIT) 16(3), 1–24 (2016) ; Ghanem, B., Glavaš, G., Giachanou, A., Paolo, S., Ponzetto, P.R., Rangel, F.: UPV-UMA at CheckThat! lab: verifying Arabic claims using a cross lingual approach. In: Working Notes of CLEF 2019 - Conference and Labs of the Evaluation Forum (2019) ; Ghanem, B., Rosso, P., Rangel, F.: An emotional analysis of false information in social media and news articles. ACM Trans. Internet Technol. (TOIT) 20(2), 1–18 (2020) ; Giachanou, A., Gonzalo, J., Crestani, F.: Propagating sentiment signals for estimating reputation polarity. Inf. Process. Manage. 56(6), 102079 (2019) ; Giachanou, A., Rosso, P., Crestani, F.: Leveraging emotional signals for credibility detection. In: Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, pp. 877–880 (2019) ; Goldberg, L.R.: A broad-bandwidth, public domain, personality inventory measuring the lower-level facets of several five-factor models. Pers. Psychol. 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Keyword:
Fact checkers detection; LENGUAJES Y SISTEMAS INFORMATICOS; Linguistic patterns; Personality traits
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URL: https://doi.org/10.1007/978-3-030-51310-8_17
http://hdl.handle.net/10251/179851
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Experimental IR meets multilinguality, multimodality, and interaction: 10th international conference of the CLEF association, CLEF 2019, Lugano, Switzerland, September 9-12, 2019, proceedings
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Opinions in Federated Search: University of Lugano at TREC 2014 Federated Web Search Track
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In: DTIC (2014)
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Concept-based semantic annotation, indexing and retrieval of office-like document units
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A Language Modelling Approach to Linking Criminal Styles with Offender Characteristics
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Evaluation of term-based queries using possibilistic ontologies
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In: Soft Computing for Information Retrieval on the Web ; https://hal.archives-ouvertes.fr/hal-03367400 ; Herrera-Viedma, Enrique; Pasi, Gabriella; Crestani, Fabio. Soft Computing for Information Retrieval on the Web, 197, Springer-Verlag, pp.135-160, 2005, Studies in Fuzziness and Soft Computing book series (STUDFUZZ), ⟨10.1007/3-540-31590-X_8⟩ ; https://link.springer.com/chapter/10.1007/3-540-31590-X_8 (2005)
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Suicide risk assessment on social media: USI-UPF at the CLPsych 2019 shared task
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