aTag:Half_truth, a User Interface to Warn of the Fallacy in the Claims Reported in the News

The half-truth fallacy—for example, quoting only parts of the data that support a writer’s argument—in the news can be fact-checked by human experts, but fact-checking takes at least a few hours during which readers can be exposed to less-than-valid arguments. As an interim solution, this study proposes the aTag:half_truth to warn of the potential half-truth fallacy before expert fact-checking. It visualises the data–assumption–claim structure and provides rebuttal comments on the information currently missing but necessary for claim validity check. The aTag:half_truth was tested using an online questionnaire for effectiveness in enhancing readers’ understanding of the issue, revealing the insufficiency of data in the original news text, and questioning the validity of the claims in the news. The analysis of data confirmed that, in the experimental group who read four fallacious claims with the aTag:half_truth, comprehension scores were higher and the scores were inversely correlated to perceived information sufficiency of news text and perceived validity of the claims. The experimental group found the aTag:half_truth rebuttal comments useful, and the percentage of the participants’ responses grounded into the rebuttal comments was significantly higher. The perceived validity of claims, however, was not significantly lower in the experimental group than in the control group for three out of four claims. Such a result was attributed to the political nature of the topics where the effects of fact-checking are limited due to readers’ interests and biases.