Abstract
The public’s concern of fake news has grown due to its potential to challenge social cohesion, and foster mistrust of the government and society in general. Recent research has revealed a concerning trend in which a sizable portion of the population has an inability to distinguish between authentic and non-authentic news, moreover in Western Balkans 75% of the population tend to believe in fake news. Writers of fake news often employ certain strategies in their articles that, from a sentiment perspective, exhibit a higher degree of polarity in comparison to authentic news articles. The rapid growth of online communities in Albania have given rise to fake news risks, however there is a limited body of research on the subject matter. In this research we will leverage the sentiment analysis techniques through feature engineering to identify the characteristics of sentiment polarity of fake news in Albanian articles.
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Muraku, B., Xiao, L., Meçe, E.K. (2024). Toward Detection of Fake News Using Sentiment Analysis for Albanian News Articles. In: Barolli, L. (eds) Advances in Internet, Data & Web Technologies. EIDWT 2024. Lecture Notes on Data Engineering and Communications Technologies, vol 193. Springer, Cham. https://doi.org/10.1007/978-3-031-53555-0_55
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