Fake News Detection Related to the COVID-19 in Slovak Language Using Deep Learning Methods

Sarnovský, Martin; Maslej-Krešňáková, Viera; Ivancová, Klaudia

doi:10.12700/aph.19.2.2022.2.3

Cited by 10 publications

(3 citation statements)

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“…The model achieved an accuracy of 91%, surpassing the performance of previous methods when applied to the same Arabic dataset. Reference [37] discussed the use of Deep Learning (DL) models to detect fake news written in Slovak, using a dataset collected from various local online news sources associated with the COVID-19 epidemic. The DL models were trained and evaluated using this dataset.…”

Section: Related Workmentioning

confidence: 99%

Fake News Classification: Past, Current, and Future

Khan,

Mehmood,

Elhadef

et al. 2023

CMC

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The proliferation of deluding data such as fake news and phony audits on news web journals, online publications, and internet business apps has been aided by the availability of the web, cell phones, and social media. Individuals can quickly fabricate comments and news on social media. The most difficult challenge is determining which news is real or fake. Accordingly, tracking down programmed techniques to recognize fake news online is imperative. With an emphasis on false news, this study presents the evolution of artificial intelligence techniques for detecting spurious social media content. This study shows past, current, and possible methods that can be used in the future for fake news classification. Two different publicly available datasets containing political news are utilized for performing experiments. Sixteen supervised learning algorithms are used, and their results show that conventional Machine Learning (ML) algorithms that were used in the past perform better on shorter text classification. In contrast, the currently used Recurrent Neural Network (RNN) and transformer-based algorithms perform better on longer text. Additionally, a brief comparison of all these techniques is provided, and it concluded that transformers have the potential to revolutionize Natural Language Processing (NLP) methods in the near future.

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Section: Related Workmentioning

confidence: 99%

Fake News Classification: Past, Current, and Future

Khan,

Mehmood,

Elhadef

et al. 2023

CMC

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“…There have been major declines in GDP, production, tourism, trade, labour and more (Adrjan & Lydon, 2021;Remenyik et al, 2020;Remeikiene & Gaspareniene, 2021). There has been a great deal of misinformation related to the pandemic, which spreads through social media rapidly (Sarnovský, 2022). In the retail sector, panic buying has been the biggest challenge, as the new situation has significantly changed the consumption habits of shoppers (Huszka et al, 2022;Sikos et al, 2021;Gyenge et al, 2021;Kitukutha et al, 2021;Csiszárik-Kocsir, 2021).…”

Section: Impact Of the Pandemic On Retailing In Hungarymentioning

confidence: 99%

Impact of teleworking on shopping habits during the COVID-19 pandemic in Hungary

Lipták¹,

Musinszki²

2022

Journal of International Studies

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The COVID-19 pandemic resulted in a sudden and unprepared switch to teleworking and home office in many workplaces and job functions. The use of teleworking in Hungary was significantly below the European average until the emergence of the coronavirus, which forced many people into this situation. Curfew restrictions have led to a complete lack of separation between work and private life for some workers, with several advantages and disadvantages. This paper aims to analyse the impact of the COVID-19 pandemic on changes in trade patterns, as confirmed by a questionnaire survey. The research is based on a questionnaire about shopping habits during the home office period. The hypothesis of the authors is that the persistence of the home office, elimination of travel for work, constant online presence, fear of the virus, and the lockdown have also significantly changed shopping habits. The survey showed that a large proportion of respondents tried to reduce the amount of personal contact during the pandemic period and most of them turned to online solutions for safety reasons. About online purchases, many respondents indicated doubts as to quality and a lack of confidence in the product they were buying. However, the positive experience gained during the pandemic period is likely to influence future purchasing habits for the majority.

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“…Various research works, applications and tools have been developed earlier to find fake news by checking the facts about the news. Most tools scrutinize the complexity as a veracity classification [2,3]. The distribution of fake news via various mediums, particularly social media platforms, cannot be stopped completely or shut down to reduce the opposing effects caused by the fake news.…”

Section: Introductionmentioning

confidence: 99%