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An Emotional Analysis of False Information in Social Media and News Articles

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An Emotional Analysis of False Information in Social Media and News Articles

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dc.contributor.author Ghanem, Bilal Hisham Hasan es_ES
dc.contributor.author Rosso, Paolo es_ES
dc.contributor.author Rangel, Francisco es_ES
dc.date.accessioned 2021-05-20T03:32:59Z
dc.date.available 2021-05-20T03:32:59Z
dc.date.issued 2020-05 es_ES
dc.identifier.issn 1533-5399 es_ES
dc.identifier.uri http://hdl.handle.net/10251/166520
dc.description.abstract [EN] Fake news is risky since it has been created to manipulate the readers' opinions and beliefs. In this work, we compared the language of false news to the real one of real news from an emotional perspective, considering a set of false information types (propaganda, hoax, clickbait, and satire) from social media and online news articles sources. Our experiments showed that false information has different emotional patterns in each of its types, and emotions play a key role in deceiving the reader. Based on that, we proposed a LSTM neural network model that is emotionally-infused to detect false news. es_ES
dc.description.sponsorship The work of the second author was partially funded by the Spanish MICINN under the research project MISMISFAKEnHATE on Misinformation and Miscommunication in social media: FAKEnews and HATE speech (PGC2018-096212B-C31). es_ES
dc.language Inglés es_ES
dc.publisher Association for Computing Machinery es_ES
dc.relation.ispartof ACM Transactions on Internet Technology es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Fake news es_ES
dc.subject Suspicious news es_ES
dc.subject False information es_ES
dc.subject Emotional analysis es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title An Emotional Analysis of False Information in Social Media and News Articles es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1145/3381750 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-096212-B-C31/ES/DESINFORMACION Y AGRESIVIDAD EN SOCIAL MEDIA: AGREGANDO INFORMACION Y ANALIZANDO EL LENGUAJE/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Ghanem, BHH.; Rosso, P.; Rangel, F. (2020). An Emotional Analysis of False Information in Social Media and News Articles. ACM Transactions on Internet Technology. 20(2):1-18. https://doi.org/10.1145/3381750 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1145/3381750 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 18 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 20 es_ES
dc.description.issue 2 es_ES
dc.relation.pasarela S\408203 es_ES
dc.contributor.funder Agencia Estatal de Investigación es_ES
dc.description.references Magda B. Arnold. 1960. Emotion and Personality. Columbia University Press. Magda B. Arnold. 1960. Emotion and Personality. Columbia University Press. es_ES
dc.description.references Bhatt, G., Sharma, A., Sharma, S., Nagpal, A., Raman, B., & Mittal, A. (2018). Combining Neural, Statistical and External Features for Fake News Stance Identification. Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW ’18. doi:10.1145/3184558.3191577 es_ES
dc.description.references Castillo, C., Mendoza, M., & Poblete, B. (2011). Information credibility on twitter. Proceedings of the 20th international conference on World wide web - WWW ’11. doi:10.1145/1963405.1963500 es_ES
dc.description.references Chakraborty, A., Paranjape, B., Kakarla, S., & Ganguly, N. (2016). Stop Clickbait: Detecting and preventing clickbaits in online news media. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM). doi:10.1109/asonam.2016.7752207 es_ES
dc.description.references Ekman, P. (1992). An argument for basic emotions. Cognition and Emotion, 6(3-4), 169-200. doi:10.1080/02699939208411068 es_ES
dc.description.references Ghanem, B., Rosso, P., & Rangel, F. (2018). Stance Detection in Fake News A Combined Feature Representation. Proceedings of the First Workshop on Fact Extraction and VERification (FEVER). doi:10.18653/v1/w18-5510 es_ES
dc.description.references Hochreiter, S., & Schmidhuber, J. (1997). Long Short-Term Memory. Neural Computation, 9(8), 1735-1780. doi:10.1162/neco.1997.9.8.1735 es_ES
dc.description.references Karadzhov, G., Nakov, P., Màrquez, L., Barrón-Cedeño, A., … Koychev, I. (2017). Fully Automated Fact Checking Using External Sources. RANLP 2017 - Recent Advances in Natural Language Processing Meet Deep Learning. doi:10.26615/978-954-452-049-6_046 es_ES
dc.description.references Kumar, S., West, R., & Leskovec, J. (2016). Disinformation on the Web. Proceedings of the 25th International Conference on World Wide Web. doi:10.1145/2872427.2883085 es_ES
dc.description.references Li, X., Meng, W., & Yu, C. (2011). T-verifier: Verifying truthfulness of fact statements. 2011 IEEE 27th International Conference on Data Engineering. doi:10.1109/icde.2011.5767859 es_ES
dc.description.references Nyhan, B., & Reifler, J. (2010). When Corrections Fail: The Persistence of Political Misperceptions. Political Behavior, 32(2), 303-330. doi:10.1007/s11109-010-9112-2 es_ES
dc.description.references Plutchik, R. (2001). The Nature of Emotions. American Scientist, 89(4), 344. doi:10.1511/2001.4.344 es_ES
dc.description.references Popat, K., Mukherjee, S., Strötgen, J., & Weikum, G. (2016). Credibility Assessment of Textual Claims on the Web. Proceedings of the 25th ACM International on Conference on Information and Knowledge Management. doi:10.1145/2983323.2983661 es_ES
dc.description.references Poria, S., Gelbukh, A., Hussain, A., Howard, N., Das, D., & Bandyopadhyay, S. (2013). Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining. IEEE Intelligent Systems, 28(2), 31-38. doi:10.1109/mis.2013.4 es_ES
dc.description.references Rangel, F., & Rosso, P. (2016). On the impact of emotions on author profiling. Information Processing & Management, 52(1), 73-92. doi:10.1016/j.ipm.2015.06.003 es_ES
dc.description.references Rashkin, H., Choi, E., Jang, J. Y., Volkova, S., & Choi, Y. (2017). Truth of Varying Shades: Analyzing Language in Fake News and Political Fact-Checking. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing. doi:10.18653/v1/d17-1317 es_ES
dc.description.references Ruchansky, N., Seo, S., & Liu, Y. (2017). CSI. Proceedings of the 2017 ACM on Conference on Information and Knowledge Management. doi:10.1145/3132847.3132877 es_ES
dc.description.references Tausczik, Y. R., & Pennebaker, J. W. (2009). The Psychological Meaning of Words: LIWC and Computerized Text Analysis Methods. Journal of Language and Social Psychology, 29(1), 24-54. doi:10.1177/0261927x09351676 es_ES
dc.description.references Volkova, S., Shaffer, K., Jang, J. Y., & Hodas, N. (2017). Separating Facts from Fiction: Linguistic Models to Classify Suspicious and Trusted News Posts on Twitter. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). doi:10.18653/v1/p17-2102 es_ES
dc.description.references Zhao, Z., Resnick, P., & Mei, Q. (2015). Enquiring Minds. Proceedings of the 24th International Conference on World Wide Web. doi:10.1145/2736277.2741637 es_ES


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