Modelling Demand for Source-Checking on Instagram: A Revealed Preference Approach
The importance of citing reputable sources is common knowledge for anyone communicating information, but less is known about whether audiences actually investigate the sources, an increasingly important practice due to the prevalence of misinformation on social media. This is a crucial determinant of whether misinformation can spread online that is often overlooked: even if there is a sufficient “supply” of credible sources, they will not be utilized if media consumers do not have sufficient “demand” for source-checking. Extending this economic analogy, this “demand” also decreases with the effort needed to check the source, analogous to the “price” of source-checking.
As such, the goal of this project is to construct an economic model of Instagram users’ demand for source-checking when faced with varying costs of doing so. This could allow us to predict how source-checking behavior changes when sources are harder to find. I hope to determine this relationship experimentally by varying the difficulty of finding the source link on informative Instagram graphics, and observing how source-checking rates change as the source becomes less accessible.
Message to Sponsor
- Major: Economics
- Sponsor: Wishek Fund
- Mentor: Stefano DellaVigna, Zheng Huang