Abstract

The authors wish to retract this Letter as follow-up work has highlighted that two errors were committed in the analyses used to produce Figs 4d and 5. In Fig. 4d, a software bug led to an incorrect value of the discriminative power represented by the blue bar. The correct value is τ = 0.17, as opposed to the value τ = 0.15 reported in the Letter. In Fig. 5, the model plot was produced with erroneous data. Produced with the correct data, the authors’ model does not account for the virality of both high- and low-quality information observed in the empirical Facebook data (inset). In the revised figure shown in the correction notice, the distribution of high-quality meme popularity predicted by the model is substantially broader than that of low-quality memes, which do not become popular. Thus, the original conclusion, that the model predicts that low-quality information is just as likely to go viral as high-quality information, is not supported. All other results in the Letter remain valid.

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