Online hate speech is a big issue, and many are worried that it leads to radicalization and actions in the real world. Here, we look at how artificial intelligence (AI) can now be used to detect hate speech and predict its impact.

1. Can Artificial Intelligence
Predict The Spread
Of Online Hate Speech?

2. © 2019 Bernard Marr, Bernard Marr & Co. All rights reserved
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IntroductionIntroduction
The rise in online hate speech and the way it is reflected in the offline world is a hot
topic in politics right now.
The internet has given everyone a voice, which clearly has positive implications for the
way citizens can publicly challenge authority and debate issues. On the other hand,
when challenge and debate spill over into attacks on minorities or vulnerable people,
there's obviously a potential for harm.
It’s fairly commonly assumed that this form of hate speech, particularly when
encountered alongside other factors such as social deprivation or mental illness, has the
potential to radicalize individuals in dangerous ways, and inspire them to commit illegal
and violent acts.
Can Artificial Intelligence Predict The Spread Of
Online Hate Speech?

3. © 2019 Bernard Marr, Bernard Marr & Co. All rights reserved
Can Artificial Intelligence Predict The Spread Of
Online Hate Speech?
Just as terrorist organizations like ISIS can be seen using hate speech in videos and
propaganda material intended to incite violence, racist and anti-Islamic material is thought
to have inspired killers like Anders Breivik, who killed 69 youths in a 2011 shooting spree,
and the 2019 Christchurch mosque shooting in which 51 died.
So far these links between online and real-world actions, though common sense tells us
they are likely to exist, have been difficult to prove scientifically. However, a piece of the
puzzle fell into place thanks to research carried out by the UN and the Universitat Pompeu
Fabra, and co-ordinated by IBM.
IBM principle researcher Kush Varshney tells me “I think the main message was that this
was the first study of its kind looking at the relationship between online and offline
behaviors, and most importantly it demonstrates why we should be taking this technical
approach to studying that relationship.”

4. © 2019 Bernard Marr, Bernard Marr & Co. All rights reserved
Can Artificial Intelligence Predict The Spread Of
Online Hate Speech?
Researchers began by compiling a list of keywords and phrases considered by
governmental agencies and NGOs to be indicators of hate speech. These included
expressions found in both Islamic-extremist and anti-Islamic posts made on Twitter and
Reddit. As the researchers validated that these words and phrases were indeed common
by searching across those platforms, they came across other co-occurring terms that were
also added to the list. Along with news reports of Islamic terrorism or anti-Islamic violence,
this list was the primary sources of data for the investigation.
This user-generated content – over 50 million tweets and 300,000 Reddit posts, made by
around 15 million users - containing these words and phrases were then classified
according to factors including their stance (Islamic-extremist or anti-Islamic), as well as the
severity of the message. The scale of severity ranged from simple use of discriminatory
language to outright incitement to violence, including genocide.

5. © 2019 Bernard Marr, Bernard Marr & Co. All rights reserved
Can Artificial Intelligence Predict The Spread Of
Online Hate Speech?
After the dataset was compiled and classified, a timeline analysis was carried out, using
machine learning to draw a picture of the correlation between the number of hate speech
messages appearing online, and a number of real-world incidents including the 2016
Orlando nightclub shooting, the 2016 Istanbul airport attack, the 2016 Finsbury Park,
London, vehicular attack and the 2016 Olethe, Kansas shooting. All of the incidents
involved Muslims or Arabs as either victims or perpetrators, and took place within 19
months.
Previously, the majority of machine learning analysis around the concept of hate speech
has focussed on building algorithms to determine whether or not particular posts or
pieces of content are hateful.
Varshney tells me “A lot of people in the machine learning community are tackling the
problem of classifying whether speech is offensive or hateful – we decided it wasn’t
important for us to tackle that problem, and often it’s a question of where you draw the
line, if something is verging on being hateful.
“What we were looking at is what’s the relationship between things that happen in the
online world, and things that happen in the real world.”

6. © 2019 Bernard Marr, Bernard Marr & Co. All rights reserved
Can Artificial Intelligence Predict The Spread Of
Online Hate Speech?
The study found that, yes, following high-profile incidents of both Islamophobic or
Islamic-extremist violence, incidents of online hate-speech do indeed increase. This didn’t
really come as a surprise to anyone as it was commonly held to be true based on casual
observation. But what was far more interesting was the fact that, in the case of Islamist-
extremist violence it wasn’t just Muslims who faced an increase in hate speech against
them, but attacks were frequently broadened to other minority groups.
Varshney told me, "The severity of the attacks also increases, so people are much more
likely to incite violence … and the target of the online messages also broadens so other
groups that have nothing to do with anything that’s happened in the real world also
experience an increase in hate speech. It could be any other group, such as homosexuals
… those were some interesting findings.”
So, is online hate speech and real-world violence a circular problem? It’s been shown that
one (real-world violence) causes the other – but is the reverse also true, creating a vicious,
self-feeding circle of hatred and violence?

7. © 2019 Bernard Marr, Bernard Marr & Co. All rights reserved
Can Artificial Intelligence Predict The Spread Of
Online Hate Speech?
Currently, that remains unclear. But proving the causal relationship between hate speech
and violence is a natural next-step for research in the field, Varshney says.
Proving this reverse relationship is likely to be more problematic, however, for a number
of reasons. Including the fact that the process of online radicalization itself is not yet well
understood from a scientific perspective. The question of how much exposure to hateful
material is needed to push a person to commit violence, over what period of time, and
how the mental health of the individual plays its part, have yet to be answered.
Varshey told me “That would probably be an even more important study to do – we didn’t
get into it in this particular project, as some of the causal relationships require techniques
that we don’t yet have.
“That inspires us to do more technical work though – and this direction is clearly a next-
step for the work, that should be done, for sure.”
The research, which can be viewed in full here, was carried out as part of IBM’s Science for
Social Good, which aimed to apply machine learning to 17 issues identified by the UN as
Sustainable Development Goals.

8. © 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2018 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website
© 2017 Bernard Marr , Bernard Marr & Co. All rights reserved
© 2019 Bernard Marr, Bernard Marr & Co. All rights reserved
Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a
strategic business & technology advisor to governments and companies. He helps
organisations improve their business performance, use data more intelligently, and
understand the implications of new technologies such as artificial intelligence, big data,
blockchains, and the Internet of Things.
LinkedIn has ranked Bernard as one of the world’s top 5 business influencers. He is a frequent
contributor to the World Economic Forum and writes a regular column for Forbes. Every day
Bernard actively engages his 1.5 million social media followers and shares content that
reaches millions of readers.
Visit The
Website

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