In recent years, false information on social media platforms has become a centre of attention due to its consequences on elections and public health. COVID-19 has shown how an infodemic fuelled by false information can be detrimental to public health. Existing measures are ineffective. Thus, the thesis takes an exploratory approach from the lens of new institutional economics. A comparative institutional analysis between public health institutions and social media platforms concerning their information discovery process and how differences between them can lead to false information on social media platforms is performed. The findings question whether false information is as widespread on social media platforms as projected, identifies the role of public health institutions and politicians in the spread of false information, how information is regulated on social media platforms and what drives the information discovery process on social media platforms. Based on the comparative institutional analysis, it is recommended to implement prediction markets to address false information on social media platforms.