Abstract:

The rapid expansion of social media platforms has transformed the way information is created, shared, and consumed. However, this digital transformation has also facilitated the unprecedented spread of fake news, particularly on platforms like Facebook and WhatsApp. The present study attempts to comparatively analyse the diffusion dynamics of fake news on Facebook and WhatsApp using a network-based and behavioural framework. A representative sample of 200 active social media users was selected through stratified random sampling. The study employed a structured questionnaire along with simulated message-tracking exercises to measure sharing behaviour, forwarding patterns, and verification tendencies. Statistical techniques such as mean, standard deviation, correlation, regression analysis, and independent sample t-test were used for data analysis. The findings reveal significant differences in the diffusion speed, network reach, and behavioural motivations of fake news sharing across both platforms. While Facebook exhibits broader and more visible cascades due to algorithmic amplification, WhatsApp demonstrates deeper penetration within closed networks due to encrypted peer-to-peer forwarding. The study concludes that platform architecture significantly influences misinformation diffusion patterns and user behaviour.

Keywords:

Fake News, Diffusion Dynamics, Social Network Analysis, Algorithmic Amplification, Forwarding Behaviour.

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Methods