The study only used a group of undergrad students. This means that the participant group had an above-average educational background which may influence the effects of misinformation correction. Additionally, future research should use a different topic for misinformation correction to increase the generalizability of the findings.

Limitations to study of Misinformation Correction across Social Media Platforms

A series of independent-samples t-tests were conducted to compare the variable results between both conditions. The results supported the meta hypothesis and showed a significant difference between the single-platform and cross-platform group. The cross-platform group expressed a higher level of vaccination certainty. The only variable that showed no significance was perceived popularity of the message.

Syracuse University

This study looks to prove the meta hypothesis that corrective messages delivered across social media platforms can lead to greater persuasive outcomes than same messages delivered by a single social media platform. The study used 251 undergraduate students for the participant group. The participants took a pretest measuring their attitudes towards vaccinations, then participants were put into either the single-platform or cross-platform condition. The single-platform group read 3 corrective messages shown on either Facebook, Twitter, or Instagram. The cross-platform group read 3 corrective messages shown on Facebook, Twitter, and Instagram. Then participants had to take a post-test measuring their attitudes towards the messages and vaccinations. Variables such as popularity perception, perceived message credibility, perceived message quality, perceived value, perceived descriptive norm, perceived injunctive norm, vaccination certainty judgements, and manipulation check were measured.

Misinformation Correction across Social Media Platforms study design and measures

Zhao, W. (2019). Misinformation correction across social media platforms. 2019 International Conference on Computational Science and Computational Intelligence (CSCI). https://doi.org/10.1109/csci49370.2019.00256 

Learn Before

Related

Learn After