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. 2021 Oct 4;11:19655. doi: 10.1038/s41598-021-99301-0

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© The Author(s) 2021

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Evolution of weekly aggregated networks by super-community, with dotted lines corresponding to the statistics across all users. (A) Diagram representing the networks collapsed to the super-community level. Edge direction represents the flow of information via retweets, i.e. from retweeted to retweeting super-community. (B) Size of the super-communities in terms of number of users. (C) Average attention per user. (D) External component of the attention toward super-communities. (E) Internal component of the attention toward super-communities. Indicated as a and b are the first and second peak in terms of network size, as shown in Fig. 4b.