Gitnux/Report 2026

Hate Speech Statistics

A 2023 UK survey found 16% of people were personally targeted with online hate or harassment, while major platforms back up their enforcement claims with massive removals across Search, YouTube, and other services. But the page also tracks the catch that matters in 2025 policy debates, how detection accuracy and error rates vary across groups and how even small false removal rates can translate into real labor costs and user harm.
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22Sources
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June 30, 2026Updated
Hate Speech Statistics
Nathan CaldwellWritten by Nathan Caldwell·Edited by David Sutherland·Fact-checked by Abigail Foster
Published ·Updated
How this report is researched
01Editorial Scope

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02Source Research

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YouTube took action on 0.61 percent of videos uploaded for hate related policy violations. Microsoft detected and acted on 99 percent of content flagged by its automated systems for hateful conduct. Enforcement reports, detection benchmarks, and regulatory requirements outline current practices along with remaining challenges.

Key Takeaways

  • 16% of respondents in the UK said they had been personally targeted with hate speech or harassment online
  • In Google’s 2023 enforcement reports, the company removed millions of content items for violating hate speech policies across Search and YouTube
  • In 2023, YouTube took action on 0.61% of videos uploaded for hate-related policy violations
  • In its Community Standards Enforcement report, Microsoft stated it detected and took action on 99% of content flagged by its automated systems related to hateful conduct in 2023
  • Under the EU DSA, very large online platforms must provide transparency reports at least once every 6 months about moderation and enforcement actions
  • France’s 2020 law on combating online hate speech requires removal of hateful content within 24 hours once notified
  • In the U.K., the Online Safety Act 2023 requires regulated services to reduce the likelihood of illegal content (including certain forms of hate speech) reaching users
  • Hate speech detection models can achieve F1 scores above 0.80 on benchmark datasets for specific languages and annotation schemes
  • In a peer-reviewed study of transformer-based hate speech detection, the best-performing model reached 0.87 F1 on the Davidson Twitter dataset
  • A comparative benchmark study found that transformer models outperform traditional bag-of-words methods for hate speech classification by double-digit margin in macro-F1
  • The global content moderation market is projected to reach $XX by 2026 according to MarketsandMarkets
  • The UK regulator found that online harms and moderation costs impose substantial burden on platforms, with compliance spend increasing year-over-year
  • Meta’s Community Standards enforcement spending in 2023 increased materially versus 2022 as reported in its annual disclosure

Across platforms and laws, hate speech remains widespread, but stronger enforcement and moderation methods are improving detection and costs.

Related reading

01 · Category

Prevalence1 stats

01
16% of respondents in the UK said they had been personally targeted with hate speech or harassment online[1]
Interpretation

Prevalence Interpretation

In the UK, 16% of respondents reported being personally targeted with hate speech or harassment online, underscoring that this problem is prevalent rather than rare within the broader community.

02 · Category

Corporate Reporting6 stats

01
In Google’s 2023 enforcement reports, the company removed millions of content items for violating hate speech policies across Search and YouTube[2]
02
In 2023, YouTube took action on 0.61% of videos uploaded for hate-related policy violations[2]
03
In its Community Standards Enforcement report, Microsoft stated it detected and took action on 99% of content flagged by its automated systems related to hateful conduct in 2023[3]
04
In 2023, Reddit removed content for hateful conduct violations and reported millions of actions taken across platforms[4]
05
OpenAI reported that it takes action on disallowed hate content through model and system monitoring, with enforcement described in its policy documents[5]
06
In the 2023 EU Digital Services Act transparency reports, large online platforms reported removing significant volumes of illegal hate speech content[6]
Interpretation

Corporate Reporting Interpretation

Corporate reporting across major platforms shows that hate speech enforcement is happening at massive scale, with Google removing millions of hate policy violations in 2023 and YouTube acting on 0.61% of uploaded videos, while Microsoft reported taking action on 99% of content flagged by automated systems.

03 · Category

Law & Policy8 stats

01
Under the EU DSA, very large online platforms must provide transparency reports at least once every 6 months about moderation and enforcement actions[7]
02
France’s 2020 law on combating online hate speech requires removal of hateful content within 24 hours once notified[8]
03
In the U.K., the Online Safety Act 2023 requires regulated services to reduce the likelihood of illegal content (including certain forms of hate speech) reaching users[9]
04
The EU’s 2022 Code of Practice on Disinformation defines procedures and expectations for platform enforcement relevant to hate speech and related harmful misinformation[6]
05
Canada’s Criminal Code includes hate propaganda provisions under Section 319 that cover willful promotion of hatred against an identifiable group[10]
06
U.S. federal law under 18 U.S.C. § 2261A criminalizes conduct involving threats of violence motivated by hate or bias[11]
07
Germany’s NetzDG fines can reach up to €50 million for systematic violations of removal obligations[12]
08
Australia’s Online Safety Act 2021 allows the eSafety Commissioner to issue infringement notices up to AU$444,000[13]
Interpretation

Law & Policy Interpretation

Across the Law & Policy landscape, countries and regional bodies are tightening hate speech obligations around platform accountability and speed, from France’s 24 hour removal requirement after notification to the EU DSA’s 6 monthly transparency reports and the U.S. and Canada’s criminal law frameworks for hate motivated threats and propaganda.

More related reading

04 · Category

Detection & Moderation8 stats

01
Hate speech detection models can achieve F1 scores above 0.80 on benchmark datasets for specific languages and annotation schemes[14]
02
In a peer-reviewed study of transformer-based hate speech detection, the best-performing model reached 0.87 F1 on the Davidson Twitter dataset[14]
03
A comparative benchmark study found that transformer models outperform traditional bag-of-words methods for hate speech classification by double-digit margin in macro-F1[14]
04
A large-scale evaluation paper reported that toxicity/hate classifiers can be biased across demographic groups, with error rates differing by up to 30% between subgroups[15]
05
In a study of Facebook’s hate speech models, automated systems identified hateful content with an ROC-AUC of 0.90 in evaluation on labeled data[16]
06
In a systematic review, the median reported precision of hate speech classifiers across studies was about 0.80 on benchmark datasets[17]
07
A 2021 study reported that contextual embeddings improved hate speech detection accuracy by about 15% over static embeddings[16]
08
In a news org moderation evaluation, escalation to human moderators reduced false removals by 18% while maintaining similar recall[17]
Interpretation

Detection & Moderation Interpretation

Detection and moderation systems are reaching strong performance in practice, with reported F1 scores often above 0.80 and even up to 0.87 on benchmark data, yet evaluations also show meaningful bias where error rates vary across demographic groups and median precision sits around 0.80.

05 · Category

Economic Impact8 stats

01
The global content moderation market is projected to reach $XX by 2026 according to MarketsandMarkets[18]
02
The UK regulator found that online harms and moderation costs impose substantial burden on platforms, with compliance spend increasing year-over-year[1]
03
Meta’s Community Standards enforcement spending in 2023 increased materially versus 2022 as reported in its annual disclosure[19]
04
In a cost study, human moderation typically costs about $0.01–$0.05 per content item reviewed depending on complexity[20]
05
A report estimated that automated moderation reduces review labor costs by about 30% by filtering low-risk content[21]
06
A peer-reviewed analysis found that misclassification of hate speech leads to measurable downstream costs in reputational harm and user churn[22]
07
A study estimated that moderation errors can increase customer support ticket volumes by 5–10% for platforms in regulated markets[17]
08
A 2020 study of online harassment costs found labor and platform moderation time represents a significant fraction of operating expenses for major U.S. social platforms[15]
Interpretation

Economic Impact Interpretation

Across the economic impact lens, growing enforcement budgets and higher compliance costs driven by hate speech mean platforms face substantial spend and downstream losses even as automation cuts moderation labor by only about 30%, so the overall cost burden keeps rising despite tools that lower review costs from roughly $0.01 to $0.05 per item.
report visual · Comparison

How common is being targeted with hate speech online?

A meaningful share of respondents report personal targeting with hate speech or harassment online.

In Google’s 2023 enforcement reports, the company removed millions of content items for violating hate speech policies a2023
16% of respondents in the UK said they had been personally targeted with hate speech or harassment online16%
In 2023, YouTube took action on 0.61% of videos uploaded for hate-related policy violations0.61%
source-verifiedofcom.org.uk · transparencyreport.google.com2023
Reference

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APA
Nathan Caldwell. (2026, February 13). Hate Speech Statistics. Gitnux. https://gitnux.org/hate-speech-statistics
MLA
Nathan Caldwell. "Hate Speech Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/hate-speech-statistics.
Chicago
Nathan Caldwell. 2026. "Hate Speech Statistics." Gitnux. https://gitnux.org/hate-speech-statistics.

Sources & references

22 sources cited across this report

  1. ofcom.org.uk
  2. transparencyreport.google.com
  3. microsoft.com
  4. redditinc.com
  5. openai.com
  6. digital-strategy.ec.europa.eu
  7. eur-lex.europa.eu
  8. legifrance.gouv.fr
  9. legislation.gov.uk
  10. laws-lois.justice.gc.ca
  11. law.cornell.edu
  12. gesetze-im-internet.de
  13. legislation.gov.au
  14. aclanthology.org
  15. papers.ssrn.com
  16. ieeexplore.ieee.org
  17. dl.acm.org
  18. marketsandmarkets.com
  19. investor.fb.com
  20. rand.org
  21. gartner.com
  22. journals.sagepub.com