A transformer-based architecture for fake news classification

Mehta, Divyam; Dwivedi, Aniket; Patra, Arunabha; Kumar, M. Anand

doi:10.1007/s13278-021-00738-y

Cited by 40 publications

(18 citation statements)

References 21 publications

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“…Aunado a esto, las fake news pueden ser políticamente motivadas (e.g., elección presidencial en USA 2016) o creadas con fines publicitarios o de mercadeo (Chen y Cheng, 2020;Mehta et al, 2021). Por ejemplo, Twitter ha sido considerada como una metáfora de la democracia puesto que la información se transmite sin intermediarios ni editores, sumado a su inmediatez en la difusión del contenido (Aparicio Moreno, 2016).…”

Section: Dinámica De Las Fake Newsunclassified

“…No obstante, Twitter y otras redes sociales también pueden minar la democracia, ya que allí, se encuentran también medios de información masivos (tradicionales), que puede usar el poder de difusión de las redes sociales para instigar la polarización y amplificar discursos autoritarios que ataquen o estigmaticen a diferentes grupos sociales (Gervais, 2015;Theocharis et al, 2016) Estas nuevas dinámicas comunicativas facilitan la difusión de información y noticias, cuyos contenidos no siempre se verifican, ya sea porque se confía en la fuente debido a su reconocimiento público (e.g., número de seguidores) o por la imposibilidad de verificar todas las noticias dado el volumen y velocidad de exposición a la información (Himma-Kadakas, 2017). Teniendo en cuenta además la proliferación de máquinas de propaganda, algoritmos sesgados, robots (bots) usados en las redes sociales para viralizar cualquier tipo de información, y sumado a la falta de regulación a nivel tanto local como global, se genera un escenario propicio para la proliferación de las fake news (Mehta et al, 2021).…”

Section: Dinámica De Las Fake Newsunclassified

“…Asimismo, parecen estar relacionadas con el surgimiento de protestas (Tucker et al, 2017), el descarrilamiento de investigaciones policiales (Starbird et al, 2014) y el ciberacoso de opositores políticos (Munger, 2017). También se han utilizado para mantener discursos e intereses políticos, desestimando medios de comunicación y cuestionando prácticas periodísticas que buscan divulgar información precisa, con el propósito de tergiversar la verdad y minar la confianza de los usuarios frente a fuentes de información confiables, lo cual dificulta determinar qué es y qué no es verdad (Brummette et al, 2018;Mehta et al, 2021;Van Duyn y Collier, 2019).…”

Section: Dinámica De Las Fake Newsunclassified

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Fact-checking on Twitter: An analysis of the hashtag #StopBulos

Lobato¹,

Velandia-Morales

Rodríguez

et al. 2021

RIP/IJP

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The fact-checking is an important tool to improve the quality of the information that circulates in virtual networks. Although there are different fact-checking verification agencies, we also found some more informal strategies such as the use of the hashtag #Stopbulos. Thus, this research aims to characterize the #StopBulos hashtag on Twitter as a way to verify information and control the spread of fake news. The results showed that there was diversity among users and the themes of the tweets that included this hashtag, while the main function was to deny fake news. However, it was found that those who achieved greater dissemination were the users with the largest number of followers and institutional character. The implications of using the #StopBulos hashtag as a tool to identify false information on social networks are discussed. Keywords: fake news, post-truth, post-news, social media, network societies

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Section: Dinámica De Las Fake Newsunclassified

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Fact-checking on Twitter: An analysis of the hashtag #StopBulos

Lobato¹,

Velandia-Morales

Rodríguez

et al. 2021

RIP/IJP

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“…Unfortunately, accessing social media easily and freely has disadvantages [ 2 ]. Many users share fake and misleading news items, which has a negative impact on society [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

“…The creators of fake news come up with clear stories in a way that the human brain cannot detect as fake. 3 Falsified news items also play an important role in critical events such as the spread of Covid-19, which has been recognized as a global pandemic [7,8]. In the Arab world, fake news has affected events taking place throughout Arabic-speaking countries.…”

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confidence: 99%

Arabic fake news detection based on deep contextualized embedding models

Nassif

Elnagar

Elgendy

et al. 2022

Neural Comput & Applic

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Social media is becoming a source of news for many people due to its ease and freedom of use. As a result, fake news has been spreading quickly and easily regardless of its credibility, especially in the last decade. Fake news publishers take advantage of critical situations such as the Covid-19 pandemic and the American presidential elections to affect societies negatively. Fake news can seriously impact society in many fields including politics, finance, sports, etc. Many studies have been conducted to help detect fake news in English, but research conducted on fake news detection in the Arabic language is scarce. Our contribution is twofold: first, we have constructed a large and diverse Arabic fake news dataset. Second, we have developed and evaluated transformer-based classifiers to identify fake news while utilizing eight state-of-the-art Arabic contextualized embedding models. The majority of these models had not been previously used for Arabic fake news detection. We conduct a thorough analysis of the state-of-the-art Arabic contextualized embedding models as well as comparison with similar fake news detection systems. Experimental results confirm that these state-of-the-art models are robust, with accuracy exceeding 98%.

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Misinformation Detection in Social Networks: A Systematic Literature Review

Duzen

Riveni²,

Aktaş³

2022

Lecture Notes in Computer Science

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A transformer-based architecture for fake news classification

Cited by 40 publications

References 21 publications

Fact-checking on Twitter: An analysis of the hashtag #StopBulos

Fact-checking on Twitter: An analysis of the hashtag #StopBulos

Arabic fake news detection based on deep contextualized embedding models

Misinformation Detection in Social Networks: A Systematic Literature Review

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