ONLINE ABUSE IN ATHLETICSAI Research Study: World Athletics Championships Budapest 23

INTRODUCTION
World Athletics has deployed Threat Matrix to protect athletes from the scourge of online abuseat the 2023 World Athletics Championships in Budapest, Hungary. This follows World Athletics’successful use of Threat Matrix to study abuse targeting athletes at the 2020 Summer Olympics
in Tokyo and 2022 World Championship in Oregon, USA. This report presents the key findings
and insights from this study.
Threat Matrix is an initiative by ethical data science company Signify Group (Signify) supported bysports investigations company Quest Global Ltd (Quest). It uses machine learning and AI Natural
Language Understanding to detect abuse and fixated threat online, helping World Athletics
understand the issues, delivering actionable, real-world solutions.
World Athletics’ deployment of Threat Matrix at the Tokyo Olympics and Oregon WorldChampionships was designed to illuminate the size, scale and gravity of the issue of online
discriminatory abuse being targeted at athletes on Twitter/X. At the World Athletics Championships
in Budapest, the analysis built on the success of the previous two events to take athlete protection
several steps further. Nearly three times the athletes were monitored compared to the World
Athletics Championships in Oregon 2022.
This report presents the findings from Budapest, highlighting the tactics used to abuse andthreaten athletes online and has formed the basis of recommendations for ongoing monitoring
and analysis, providing an updated blueprint detailing solutions to protect athletes at all times,worldwide.

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METHODOLOGYTo protect athletes and gain an understanding of online abusesurrounding the 2023 World Athletics Championships, the ThreatMatrix team monitored the accounts of 1,344 competitors acrosssocial media platforms Twitter/X and Instagram.

157,061

Tweets captured foranalysis

The 1,666 active athlete accounts across Twitter/X or Instagram,representing 1,344 athletes, were derived from a list of 2,195
athletes provided by World Athletics ahead of the championships.
Threat Matrix’s monitoring began on August 18th and ended
August 28th, taking in the duration of the 2023 World Athletics
Championships in Budapest, Hungary. The timeframe was designed
to detect any abuse in the run-up to and fall-out from the WorldChampionships, as well as abuse during the event itself.
After the Threat Matrix linguistic filters removed any identified spam,
the team captured 449,209 posts and comments on Twitter/X andInstagram for review. For the purposes of Threat Matrix, a poston Twitter/X refers to any tweet in which an athlete’s @ handle ismentioned. On Instagram, a comment refers to any comment madein response to an organic in-feed upload by an athlete.
The team then used text analysis to search for slurs, weaponised
emojis and other phrases that could indicate abuse. Image recognition
tools were also deployed to identify offensive images. AI-powered
Natural Language Processing was also applied to detect threats byunderstanding the relationships between words. This allows Signify
to determine the difference between, for example, ‘I’ll kill you’ and‘You killed it’.

292,148

Instagram comments
captured for analysis

1,344

athletes selected formonitoring with 1,666
active accounts(from a list of 2,195
provided by WorldAthletics)

1 SOURCE DATA

3 ANALYSE DATA

2 CLEAN DATA

4 EVIDENCE + ACTION

Using AI-powered threat detection
algorithm, Signify scan public posts

Flagged posts are analysed by Signify’s
team of experts

Removing bots, discriminatory abusetargeting selected athletes is flagged

The most egregious examples of abuse
are prepared and submitted for action

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KEY FINDINGS
Analysis of the monitoring period identified clear instances of online abuse and threat, targeting
athletes at the 2023 World Athletics Championships. Threat Matrix detected notable examplesof racist and sexualised abuse, with a selection of posts extending into potential action from law
enforcement.
The levels of abuse detected in Budapest were noticeably higher when compared with the similar
study at the 2022 World Athletics Championships, even allowing for the increased number ofathletes monitored, however the number of targeted athletes was only a third higher, meaning
those targeted experienced more intense focus. The Budapest championships saw more than fourtimes the abuse targeting an increased dataset of 47 athletes.
Further comparisons between Budapest 2023 and Oregon 2022 will be made later in this report.
However, key findings from this latest study are as follows:••••Racism and sexualised abuse continue to be used to target athletes – over 51% of all abusedetected during the analysis period came from one of these categories
X was the preferred channel for abusers, accounting for almost 90% of detected abuse – a500% relative increase from 2022
Unlike previous tournaments where abuse was driven by events outside the stadium, mostabuse was targeted at athletes based on their wider reputations or comments they made at
the championships, particularly in relation to the media
Two athletes were the most heavily targeted athletes in the selection, accounting for around
44% of detected abuse between them.

258

4735%

16%

90%

46%

abusive posts wereidentified coming from 237
unique authorsof identified abuse wassexual or sexist in natureof the 1,344 tracked
athletes received targetedabuseof detected abuse wasmade on X (formerlyTwitter)4of identified abuse wasracist in natureof athletes who wereabused in the analytics
came from the USA

PLATFORM BREAKDOWN
Platform coverage for 1,344 athletes found 1,666 active accounts.
X (formerly Twitter) had 374 active accounts – representing 22.5%
Instagram had 1,292 accounts – representing 77.5%
This split is the inverse of detected abuse.
(See page 9 for comparisons with Oregon 2022).

Breakdown of detected abuseby platform

374

1,292

250

200

Breakdown of active accounts
by platform

150

100

5005

ANALYSIS OF ABUSEIn the analysis of detected abuse, the most frequent types of abuse were racism and sexualisedcomments – comprising over 56% of all abuse during the monitoring timeframe.
Together, sexualised and sexist abuse – overwhelmingly targeted at female athletes – made up
over 21% of all detected posts.
In an evolution of previous analysis, racism was not only a form of abuse but an allegation levelled
at athletes, particularly black athletes. This was frequently used as a mask for the posters’ own
racism.
Unfounded doping allegations were used as the springboard and justification for other forms ofabuse.

Most common types of abuse
by gender

Women
Men

Percentage of total abuse

35%

Racism16%

Sexual15%

General abuse

Homophobia

9%5%

Sexism6

TRIAGE ANALYSIS OF ABUSE
As part of this analysis, a detailed triage was applied to all flagged
abuse, with the content and context of each message assessed andcategorised into a set of tiers according to the gravity of abuse andthe recommended actions.
Similarly, the Threat Matrix service assesses all flagged posts andcomments for threat. Across this dataset, there was nothing deemed
as imminent threat (by contrast to previous events), in accordancewith Threat Matrix proprietary indicators for fixated threat. No cases
were identified for immediate escalation to law enforcement.
The majority of cases contained language that was abusive but
required no further action. 33% of the abuse was escalated to theplatforms for additional action and 14% of the abuse was deemedsuitable for both platform action and assessment by World Athletics
of possible further action up to and including assessment ofappropriateness of jurisdictional law enforcement involvement.

TIER 2
14%

TIER 133%

TIER 053%

7TIER 0Flag to World
Athletics

TIER 1

Report toplatform + World
Athletics

TIER 2

Report toplatform + World
Athletics +assess for law
enforcement

EVENT COMPARISON

300

Threat Matrix’s studies for the 2020 Summer Olympics inTokyo and World Athletics Championships in Oregon 2022analysed almost 250,000 and 428,000 posts respectively
targeting a representative sample of 161 athletes and officials/
media personalities in Tokyo and 458 in Oregon.

250

For Budapest this was increased to cover 1,344 athletes andofficials/media personalities with accounts and resulted in449,209 posts and comments being analysed.
Given the different range of accounts monitored it is hard to
draw detailed comparison between the three events. However,there are useful trends that can be detected.

200

In Tokyo the process detected 132 posts flagged as abusivefrom 119 authors, targeting 23 athlete accounts.

However, the figures for the 2020 Olympics are influenced
by two athletes receiving almost 65% of all abuse during theTokyo Games. When the abuse targeting those athletes is
stripped out, similar volumes can be observed across the twoevents.

150

verified/detected abuse

In comparison, the volume of abuse targeting athletes at the2022 World Athletics Championships appears much lower.
59 abusive posts were detected against a much larger set ofathlete accounts.

100

At Budapest in 2023 nearly 260 cases of abuse weredetected, almost double the number of incidents in Tokyo and5x the number detected in Oregon. However, there are several
factors to consider in drawing conclusions.
Both Tokyo and Budapest saw two athletes account for themajority of abuse and highlight the fact that abuse often
follows abuse with more abusers joining in once an athlete
has been singled out. Secondly, Tokyo saw over half as muchabuse from a far smaller sample set showing the profile that anOlympic Games brings.

500Tokyo
2020

8Oregon Budapest
2022
2023

Considering the relevant number of athletes monitoredfor each competition this represents a small rise but
is a consistent level of abuse with the previous World
Athletics Championships. Budapest also saw a far higher
number of individual athletes receive abuse highlighting
the importance of monitoring all athletes.
Analysis of platform breakdowns between Oregon andBudapest shows a stark increase in Twitter/X cases but
a consistent level of Instagram abuse. This illustrates twopoints:

250

200

1. Twitter/X remains the pre-eminent platform forwatching live events and therefore abusing athletes
in real time, and Instagram use is evolving amongstathletes.
2. Far fewer athletes post during competition timelending an atmosphere of stasis to their accounts– those that do often only do so to celebrate
success, and many employ some form of comment
management where platforms allow.

150

As the study shows abuse and threat are still getting
through to athletes on Instagram, but it is not the primary
platform of choice for attacking athletes, which the data
indicates remains Twitter/X.

100

This is relevant to note as it suggests World Athletics
faces a consistent issue of online abuse targeting athletes
at major events. However, the ability to detect and reportthese to their respective platforms demonstrates theavailability of solutions and protective measures that canbe deployed.

500Oregon
2022

9

Budapest
2023

CONCLUSION
This study represents the third deployment of Threat Matrix’s AI-powered methodology following
previous reports covering the Tokyo 2020 Olympic Games and the 2022 World Athletics
Championships in Oregon. Alongside continuing to highlight the prevalence of abuse targeting
athletes at a range of events across multiple years the report is also the first that allows us to draw
like-for-like comparisons on two editions of the same event.
The expansion of athlete coverage for Budapest 2023 has shown that the number of athletes
targeted during a competition can run deep, however, the competition saw a handful of athletes
singled out to receive the majority of abuse.
This is significant as it represents both a need and opportunity to shape the way in which athlete
welfare is handled during and after competitions. There is an opportunity to pre-emptively
intervene with athletes who are being targeted – ahead of a spike of abuse/pile-on occurring.
Threat Matrix analysis has also shown similar issues continue to plague athletes in terms of abusefrom Tokyo 2020 and Oregon 2022. There continues to be a significant portion of racist abuse,
while female athletes continue to face sexualised and sexist comments online.
Homophobic abuse continues to be prevalent but has evolved to encompass more than justtargeting those who have publicly declared their sexuality, perceived by the authors as one of themost insulting allegations that can be thrown at an athlete, particularly male athletes.
Detecting abuse among the millions of tweets and comments directed at athletes requires AIenabled solutions and a specialist expertise. Having these abusive posts taken down by platforms
is, however, just the first step. Threat Matrix has also continued to demonstrate through its triage,
analysis, and investigative work that accounts behind this abuse can be uncovered and – in manycases – deanonymised, paving the way for real-world action that, in the long-term, will build
deterrence and show abusers they cannot behave in this way without facing consequences.
Whilst the data clearly shows that Twitter/X remains the pre-eminent platform for those engaging‘live’ with events such as athletics, seeing by far the most abusive content during or on theimmediate wake of events, Instagram contains a higher proportion of serious abuse, often coming
later and in a more calculated fashion than Twitter/X abuse.
It is also clear that despite many athletes not posting frequently on social media during competition
time – if at all – and limiting or managing who can comment, serious abuse, is still getting throughand requires monitoring to ensure it is not left unchallenged.
Feeding back to the platforms and acting in partnership with them will be essential in enacting thegoals of this report.
Threat Matrix and World Athletics will continue to work with the platforms to be able to highlight
this and work towards ending the scourge of abuse targeting athletes on their channels.

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APPENDIX: DETAILED METHODOLOGYCHANNELS AND MEDIA FORMATS
This study focuses on discriminatory abuse and threats captured on Twitter/X and Instagram in arange of media formats:••••Text, including word matches denoting abuse or threatEmojis
Images, whether symbolic or text within images
Voice notes

DEFINITION OF ABUSE
Our definition of abuse is based on the inclusion of a reference, whether express or implied, toany one or more of the following: ethnic origin, colour, race, nationality, religion or belief, gender,gender reassignment, sexual orientation or disability.
As a priority, we look for any threatening comments and those which take a similarly abusive or
threatening aspect towards an athlete or an athlete’s family.
For this study, we also incorporated additional categorisations of possible abusive terminologies,associated specifically to Athletics. These include narratives around doping allegations andtransphobia.

SCOPE
The primary focus of this study has been public posts on Twitter/X and public comments made to
selected athletes on Instagram.
Guided by World Athletics, we have worked with a selection of 2,195 athletes and officials / media
personalities, from which 1,344 had at least one of an active Twitter/X or Instagram account.

11SCALE + COVERAGE
We examined 449,209 posts across Twitter/X and Instagram matching our inclusion criteria.
••••

Posts mentioning an athlete by handle
English language or Emoji
A small amount of Spanish language abuse was also flagged by Threat Matrix
Posts mentioning 2 or fewer separate handles, to filter out spam and long conversations
which often have little relevance towards the individual tagged people

We examined 449,209 posts across Twitter/X and Instagram matching our inclusion criteria.
Most of the abusive posts were detected by our text analysis algorithm, which flags posts on thebasis of over 500 keywords, phrases and emojis.
This flagged over 8,321 posts for further review, which were then individually assessed to see ifthey met abuse criteria.
In addition to this, we use an AI-empowered threat algorithm to determine posts that contained
explicitly threatening language.

LANGUAGE
The Threat Matrix service operates a multi-lingual filter set, with specialist keywords (as wellas emojis), representing different caterisations of abuse, discrimination and threat. The service
includes 32+ languages (including the following):
Argentine Spanish

Filipino

ItalianSerbianAustralian Slang

FrenchJapanese

SlovakianBrazilian Portguese

French Canadian

KoreanSpanish

ChineseGeorgian

NorwegianSwedishCroatianGermanPersian

TurkishDanishHaitian Creole

PolishVietnamese

Dutch

Hebrew

Russian

Xhosa

EnglishHungarian

SamoanZulu

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