Researchers at the Massachusetts Institute of Technology found that fake news spreads faster on Twitter than real news. Increased digital use has led to spread of fake news on social media platforms, especially on Twitter, where a single tweet can instantly form a flow of information. The present study investigated the underlying factors that could contribute to the spread of fake news on Twitter during socio-economic crises by referring to the Rumor theory as its theoretical foundation. The socio-economic crises under analysis in this study are the COVID-19 Anti-Vaccination Movement, and the exacerbated Australian Bushfire Crisis, which both have affected businesses and enterprises on a large scale. By utilizing Twitter API, relevant tweets during the said socio-economic crises were collected and these factors determined how tweets were coded: anxiety, ambiguous source, ambiguous content, user’s personal involvement, and social interactions. Finally, logistics regression analysis took place to predict the likelihood of fake news spread due to the factors mentioned. The aim of this research is to uncover what factors contribute to spread of fake news, as well as discern the most significant factor that could lead to spread of fake news on social networking platforms - specifically on Twitter.

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