Fake news in business and management literature: a systematic review of definitions, theories, methods and implications

Farhoudinia, Bahareh; Ozturkcan, Selcen; Kasap, Nihat

doi:10.1108/ajim-09-2022-0418

Cited by 5 publications

(1 citation statement)

References 106 publications

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“…However, relying on SM platforms for ESCM is not sufficient for firms to boost the effectiveness of environmental campaign during and post-COVID-19 time. It is because the propagation of fake news on SM has been a critical alarm with extensive effects, and this alarm has been intensified during pandemic, which can cause severe effects on marketing products, firms, and consumer behaviours (Farhoudinia et al. , 2023).…”

Section: Literature Review and Hypothesesmentioning

confidence: 99%

The role of firms’ communication about eco-friendly products on social media and conventional media post-COVID-19

Koswara,

Trulline,

Rohman

2024

JCOM

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PurposeThe paper examined the impact of corporate communication about eco-friendly products on social media (CSM) and conventional media (CCM) on individuals/buyers’ intent for co-creating environmental values (ICEV) post-Coronavirus pandemic in Indonesia.Design/methodology/approachData were gathered from 561 individuals/buyers, via cross-sectional sampling in Bandung city, Indonesia. Next, this study used structural equation modelling to assess the theoretical model and hypothetical relationships.FindingsBoth factors, i.e. CCM and CSM, positively and significantly affect ICEV.Originality/valueThe paper is an original attempt to assess the impact of corporate communication about eco-friendly products on media toward ICEV in Indonesia’s post-Coronavirus pandemic. Besides, it is an initial effort to create the notions of success expectancy and self-efficacy and analyse whether these two concepts can become factors that mediate the effects of corporate CCM and CSM on buyers’ ICEV. This paper also develops ICEV to expand social cognitive theory from the perspective of co-creating environmental values.

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Section: Literature Review and Hypothesesmentioning

confidence: 99%

The role of firms’ communication about eco-friendly products on social media and conventional media post-COVID-19

Koswara,

Trulline,

Rohman

2024

JCOM

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Determinants of multimodal fake review generation in China’s E-commerce platforms

Liu,

He,

2024

Sci Rep

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This paper develops a theoretical model of determinants influencing multimodal fake review generation using the theories of signaling, actor-network, motivation, and human–environment interaction hypothesis. Applying survey data from users of China’s three leading E-commerce platforms (Taobao, Jingdong, and Pinduoduo), we adopt structural equation modeling, machine learning technique, and Bayesian complex networks analysis to perform factor identification, path analysis, feature factor importance ranking, regime division, and network centrality analysis of full sample, male sample, and female sample to reach the following conclusions: (1) platforms’ multimodal recognition and governance capabilities exert significant negative moderating effects on merchants’ information behavior, while it shows no apparent moderating effect on users’ information behavior; users’ emotional venting, perceived value, reward mechanisms, and subjective norms positively influence multimodal fake review generation through perceptual behavior control; (2) feature factors of multimodal fake review generation can be divided into four regimes, i.e., regime 1 includes reward mechanisms and perceived social costs, indicating they are key feature factors of multimodal fake review generation; merchant perception impact is positioned in regime 2, signifying its pivotal role in multimodal fake review generation; regime 3 includes multimodal recognition and governance capabilities, supporting/disparaging merchants, and emotional venting; whereas user perception impact is positioned in regime 4, indicating its weaker influence on multimodal fake review generation; (3) both in full sample, male sample, and female sample, reward mechanisms play a crucial role in multimodal fake review generation; perceived value, hiring review control agency, multimodal recognition and governance capabilities exhibit a high degree of correlation; however, results of network centrality analysis also exhibit heterogeneity between male and female samples, i.e., male sample has different trends in closeness centrality values and betweenness centrality values than female sample. This indicates that determinants influencing multimodal fake review generation are complex and interconnected.

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Emotions unveiled: detecting COVID-19 fake news on social media

Farhoudinia,

Ozturkcan,

Kasap

2024

Humanit Soc Sci Commun

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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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Fake news in business and management literature: a systematic review of definitions, theories, methods and implications

Cited by 5 publications

References 106 publications

The role of firms’ communication about eco-friendly products on social media and conventional media post-COVID-19

The role of firms’ communication about eco-friendly products on social media and conventional media post-COVID-19

Determinants of multimodal fake review generation in China’s E-commerce platforms

Emotions unveiled: detecting COVID-19 fake news on social media

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