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. 2020 Sep 1;10:14392. doi: 10.1038/s41598-020-71231-3

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Size of the largest connected component for the sentiment-based attacks in Twitter (A) and in Gab (B). Each curve corresponds to the sentiment targeted for the removal. (C) Correlation between the sentiment score and the degree of the nodes. The corresponding sentiment is written in the vertical axes. For the sake of clarity, in Twitter networks we only plot a random $20 %$ selection of all users.