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- Farhoudinia, Bahareh, et al.
(författare)
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Emotions unveiled : detecting COVID-19 fake news on social media
- 2024
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Ingår i: Humanities and Social Sciences Communications. - : Springer Nature. - 2662-9992. ; 11:1
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Tidskriftsartikel (refereegranskat)abstract
- The COVID-19 pandemic has highlighted the pernicious effects of fake news, underscoring the critical need for researchers and practitioners to detect and mitigate its spread. In this paper, we examined the importance of detecting fake news and incorporated sentiment and emotional features to detect this type of news. Specifically, we compared the sentiments and emotions associated with fake and real news using a COVID-19 Twitter dataset with labeled categories. By utilizing different sentiment and emotion lexicons, we extracted sentiments categorized as positive, negative, and neutral and eight basic emotions, anticipation, anger, joy, sadness, surprise, fear, trust, and disgust. Our analysis revealed that fake news tends to elicit more negative emotions than real news. Therefore, we propose that negative emotions could serve as vital features in developing fake news detection models. To test this hypothesis, we compared the performance metrics of three machine learning models: random forest, support vector machine (SVM), and Naïve Bayes. We evaluated the models’ effectiveness with and without emotional features. Our results demonstrated that integrating emotional features into these models substantially improved the detection performance, resulting in a more robust and reliable ability to detect fake news on social media. In this paper, we propose the use of novel features and methods that enhance the field of fake news detection. Our findings underscore the crucial role of emotions in detecting fake news and provide valuable insights into how machine-learning models can be trained to recognize these features.
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| 2. |
- Farhoudinia, Bahareh, et al.
(författare)
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Fake news in business and management literature : A systematic review of definitions, theories, methods, and implications
- 2023
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Ingår i: Aslib Journal of Information Management. - : Emerald Group Publishing Limited. - 2050-3806 .- 2050-3814.
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Tidskriftsartikel (refereegranskat)abstract
- This paper aims to conduct an interdisciplinary systematic literature review of fake news research and to advance the socio-technical understanding of digital information practices and platforms in business and management studies. The paper applies a focused, systematic literature review method to analyze articles on fake news in business and management journals from 2010 to 2020. The paper analyzes the definition, theoretical frameworks, methods, and research gaps of fake news in the business and management domains. It also identifies some promising research opportunities for future scholars. The paper offers practical implications for various stakeholders who are affected by or involved in fake news dissemination, such as brands, consumers, and policymakers. It provides recommendations to cope with the challenges and risks of fake news. The paper discusses the social consequences and future threats of fake news, especially in relation to social networking and social media. It calls for more awareness and responsibility from online communities to prevent and combat fake news. The paper contributes to the literature on information management by showing the importance and consequences of fake news sharing for societies. It is among the frontier systematic reviews in the field that cover studies from different disciplines and focus on business and management studies.
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| 3. |
- Farhoudinia, Bahareh, et al.
(författare)
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Lexicon-based sentiment analysis of fake news on social media
- 2022
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Ingår i: Presented at the AIRSI2022 Conference: Technologies 4.0 in Tourism, Services & Marketing, Zaragoza, Spain, July 11-13, 2022, Zaragoza, Spain, 2022. - Zaragoza, Spain.
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Konferensbidrag (refereegranskat)abstract
- Social media is considered one of the primary sources of information. Besides all benefits that social media bring to human life, the popularity of social media simultaneously caused a rapid spread of fake news. Fake news poses a serious threat to societies since it enhances the polarity among different ideas, such as political parties. The fake news issue was further exacerbated during the COVID-19 Pandemic, and fake news studies attracted the attention of plenty of researchers (e.g., Apuke & Omar, 2021; Elías & Catalan-Matamoros, 2020). For example, Fake news claiming that 5G cell towers affect the human immune system has led to the burning of some cell towers in Europe (Mourad et al., 2020). Researchers claimed that fake stories spread more rapidly than true ones on social media (Vosoughi et al., 2018). The rapid spread of fake news makes companies and organizations vulnerable. Fake news about a company can directly affect the company's stock price and cause financial losses. A literature review reveals that scholars from multidisciplinary areas are interested in this topic; for instance, psychology scholars aim to answer research questions such as why people believe and share fake news (Talwar et al., 2019) and what are the characteristics of people who share or are involved in the spread of fake news (Ben-Gal et al., 2019; Brashier & Schacter, 2020). Computer science scholars aim to find ways to detect fake news, using machine learning techniques to create detection models (Faustini & Covões, 2020; Ozbay & Alatas, 2020). Emotion and sentiment analysis of fake news have not been studied in the literature; thus, this research will contribute to the field significantly.
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