Abstract
In Singapore, there has been a rise in misinformation on mobile instant messaging services (MIMS). MIMS support both small peer-to-peer networks and large groups. Misinformation in the former may spread due to recipients’ trust in the sender while in the latter, misinformation can directly reach a wide audience. The encryption of MIMS makes it difficult to address misinformation directly. As such, chatbots have become an alternative solution where users can disclose their chat content directly to fact checking services. To understand how effective fact checking chatbots are as an intervention and how trust in three different fact checkers (i.e., Government, News Outlets, and Artificial Intelligence) may affect this trust, we conducted a within-subjects experiment with 527 Singapore residents. We found mixed results for the fact checkers but support for the chatbot intervention overall. We also found a striking contradiction between participants’ trust in the fact checkers and their behaviour towards them. Specifically, those who reported a high level of trust in the government performed worse and tended to follow the fact checking tool less when it was endorsed by the government.
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Notes
- 1.
Non-Halal food do not follow the dietary observances of Islamic law and Muslims are prohibited from consuming them.
- 2.
TGM Research (https://tgmresearch.com/) was engaged for the recruitment of participants.
- 3.
Multiple responses made by the same participant (identified by their participant identification number) were removed.
- 4.
Responses in which the participant gave identical answers to each series of questions in the experiment were removed.
- 5.
- 6.
Repeated measures ANOVA assumes sphericity by default, which is the condition that the variances of the differences between all possible pairs of a given within-subject independent variable are equal. If the assumption of sphericity is violated, we might end up with inflated F-scores and Greenhouse–Geisser corrections are applied to produce a more valid F-score.
- 7.
When performing post hoc analysis, we encounter the multiple comparisons problem. When using simultaneous statistical tests, each test has a potential to produce an effect, leading to Type I errors (incorrectly rejecting the null hypothesis, and thus incorrectly accepting an effect that is not there). To counter this issue, we use Bonferroni corrections, in which the p-value is multiplied by the number of pairwise comparisons to be made.
- 8.
Friedman test is an alternative to repeated measures ANOVA which does not require normally distributed data, and is suitable for interval data, e.g., discrete scales like a Likert scale.
- 9.
Wilcoxon signed-rank test is an alternative to paired t-tests, which does not require normally distributed data, and is suitable for interval data. The Bonferroni correction is applied to prevent the multiple comparisons problem as explained in footnote 7.
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Lim, G., Perrault, S.T. (2023). Fact Checking Chatbot: A Misinformation Intervention for Instant Messaging Apps and an Analysis of Trust in the Fact Checkers. In: Soon, C. (eds) Mobile Communication and Online Falsehoods in Asia. Mobile Communication in Asia: Local Insights, Global Implications. Springer, Dordrecht. https://doi.org/10.1007/978-94-024-2225-2_11
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