Snode Technologies asks whether data can predict random acts of violence

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Watch the news or scroll your social media feed lately, and it looks as if the number of violent acts across the globe are on the rise.

In the United States for example there has been a sharp spike in the number of mass shootings in 2019, and locally xenophobic attacks threaten to destabilise relations between African countries. Added to this are a rise in terrorist attacks like the ones perpetrated in Christchurch and Colombo.

This has prompted Nithen Naidoo, CEO of Snode Technologies to ask a very intriguing question – why didn’t anyone see it coming?

Turning to social media

Naidoo ponders this problem as he has highlighted a specific golden thread linking many of these acts of violence, with most of the perpetrators behind them being galvanised on social media.

“In Texas, the 21-year-old gunman charged with killing 22 people at an El Paso Walmart had drafted a lengthy anti-immigrant manifesto, describing his plans and political motivation for the attack, and posted it online 20 minutes before the incident. Prior to streaming the mass murder on Facebook Live, the gunman who killed 50 people in a mosque in Christchurch, New Zealand, posted his hate-filled manifesto online, along with images of the weapons he used in the attack. The highly politicised #FeesMustFall movement of 2015 ground academia to a halt in the pursuit of social justice, spurred on by discord online,” notes the Snode CEO.

“The sheer volume of sentiment from people across the globe begs the question: can data collected from social media predict random acts of violence? ,” he asks.

Naidoo is careful to stress that social media does not pertain to popular sites like Twitter and Facebook alone, especially as many of these inciters of violence could be vocal on lesser known platforms where potentially dangerous behaviours such as cyber-bullying, hacktivism and terrorism narratives are rife.

As such the CEO says dynamic data can empower proactive policing, medical emergency response, disaster relief, disease control and national defence. By employing digital defence strategies, it is possible to prevent these incidences from manifesting, and ultimately change the course of history, he points out.

Empowering prediction

He believes that using technology that augments human intelligence allows companies to interpret digital data at internet-scale, and in so doing, identifies patterns that could empower prediction.

“Open data sources, such as social media, are a renewable source of energy that drives our analytical capability. Our machine learning algorithms learn from every tweet, post, like and dislike – painting a picture of public perception and sentiment. The trending patterns of negative sentiment – combined with multiple attributes of each individual – can be indicative of a growing potential for an outbreak of violence. This forecasting of emerging threats helps emergency response teams to manage and contain risk exposure,” Naidoo explains.

In particular the Snode CEO is of the opinion that technologies like this should not exist in isolation, but rather form part of an integrated, multifaceted strategy in order to accurately predict behaviour.

“Such innovation does not abandon traditional or conventional response processes – it simply enriches them with real-time tools for rapid data-driven decision making. This asymmetric response capability discourages and disenfranchises attackers, kidnappers, organised crime and perpetrators of social unrest. Digital defence systems offer numerous ways to counter the criminal advantage – putting the power back in our hands,” he concludes.

[Image – Photo by Pawel Janiak on Unsplash]

Robin-Leigh Chetty

Robin-Leigh Chetty

Editor of Hypertext. Covers smartphones, IoT, 5G, cloud computing and a few things in between. Also a keen photographer and dabbles in console games when not taking the hatchet to stories.


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