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Human Detection of Illegal Content Online, by Flagging Reason (2017-2021)

The chart shows the distribution of the videos removed by Youtube based on human detection, by flagging reason. The data represents average shares of videos removed for the period October 2017-March 2021 and are calculated based on the trimestrial values included in the transparency report. The results show that the users' main flagging reason of videos is the spam, mislinding and scam content, followed by sexual content and hateful or abusive content. When flagging a video, human flaggers can select a reason they are reporting the video and leave comments or video timestamps for YouTube's reviewers. This chart shows the flagging reasons that people selected when reporting YouTube content. A single video may be flagged multiple times and may be flagged for different reasons. Reviewers evaluate flagged videos against all of the Community Guidelines and policies, regardless of why they were originally flagged. Flagging a video does not necessarily result in it being removed. Human flagged videos are removed for violations of Community Guidelines once a trained reviewer confirms a policy violation.
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Number of Videos Removed by Google Under Their Child Safety Policy

The chart shows the number of videos removed by Google under their Child Safety policy, starting from September 2018. The latest available data shows a 34% increase of videos' removal compared to the previous trimester.
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Number of Web Pages containing Adverts or Links to Child Sexual Abuse Material

The chart provides information on the number of web pages containing adverts or links to child sexual abuse imagery, according to the age of children. The data shows an increase of these web pages in 2019 by 26% compared to 2018 and by 70% compared to 2017.
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Percentage of Active False Posts With No Direct Warning Label

The chart shows the percentage of posts in Reuters Institute's sample rated as false that were still active and did not have a clear label at the end of March 2020 (Twitter: (N=43; YouTube: N=6; Facebook: N=33) out of the total number of posts on each platform in the sample (Twitter: N= 73; YouTube: N= 22; Facebook: N=137).
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Percentage of Content Found by Facebook as Containing Adult Nudity and Sexual Activity Compared to the Content Reported by the Users

This chart shows the percentage of content found by Facebook as containing adult nudity and sexual activity compared to the content reported by the users. As the result shows, the percentage of content actioned that Facebook found and flagged before users reported it is significantly higher that the one reported by users.
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Percentage of Content Found by Facebook as Containing Child Nudity and Exploitation Compared to the Content Reported by the Users

This chart shows the percentage of content found by Facebook as containing child nudity and exploitation compared to the content reported by the users. The percentage reported by users is significantly lower that the one found by Facebook.
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Percentage of Content Found by Facebook as Containing Spam Compared to the Content Reported by the Users

This chart shows the percentage of content found by Facebook as containing spam compared to the content reported by the users. As the results show, almost all of the content containing spam was first found by Facebook (the percentage remains between 99.7% and 99.9% for the whole period).
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Percentage of Content Found by Instagram as Containing Child Nudity and Exploitation Compared to the Content Reported by the Users

This chart shows the percentage of content found by Instagram as containing child nudity and exploitation compared to the content reported by the users. The percentage reported by users is significantly lower that the one found by Instagram.
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Percentage of Content Found by Instagram as Hate Speech Compared to the Content Reported by the Users

This chart shows the percentage of content found by Instagram as containing hate speech compared to the content reported by the users. The data shows a significant improvement of hate speech detection of Instagram in the second part of 2020.
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Reconfigured versus Fabricated Misinformation

The chart shows the proportion of reconfigured (N=133) and fabricated (N=86) misinformation in the sample (N=225) and the types of misinformation that constitute both reconfigured and fabricated misinformation. Out of the share of the content showed above, 59% is reconfigured (out of misleading, false context and manipulated content) and 38% is fabricated (out of fabricated and imposter content).