Getting ahead of the crowd – social media intelligence transforms policing of events

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Incidents that cause disruption and threaten public safety at mass-attendance public events serve as a reminder of the significant challenges police forces face.

Such disturbances often spark confusion and the fear that a serious incident, such as terrorism, is underway – which can lead to mass over-reaction. And although violence may occur at protests and marches, its nature and motivation varies. Instead of being motivated by religious or political extremism, violence may in fact be the result of resentment towards the police or event organisers.

To understand the exact motivation of these criminals and pinpoint the origin of an attack as well, investigators can tap into social media intelligence (SOCMINT). But in a world where social media seamlessly integrates into our everyday lives, the value of SOCMINT as an intelligence source extends much further.

In many investigations, intelligence teams use publicly available social media data to validate what they know and surface new leads. SOCMINT specifically focuses on extracting intelligence and insights from social media platforms including mainstream platforms, niche platforms and country-specific sites. This is especially valuable during live events, where timely collection and analysis help identify risks and relevant activity as they unfold.

Inadequate responses or heavy-handed approaches are more likely without intelligence

Without accurate intelligence, it is challenging for policing agencies to match resources to the level of risk posed by events – especially when only loosely coordinated by their organisers. The most obvious example, which had long-term consequences for US society, was the policing of the protest at the Capitol in January 2021 following the election result.

Conversely, the value of proactive intelligence is shown by the success of Operation Venetic, the UK’s intelligence-led response to the covert infiltration of the EncroChat criminal comms network. The country’s National Crime Agency (NCA) took in the EncroChat intelligence; sifted, triaged and analysed the data, then created intelligence packages that identified UK-based organised crime groups, handles, phones, locations and crime types.

These examples clearly highlight the potential value of proactive intelligence to the police to support planning and risk mitigation.

Traditional security processes fall short

Traditional event security measures are no longer sufficient, as the nature of event security has become more complex than ever, with evolving threats on both physical and digital fronts. Police teams must gather as much information as possible from social media, which is where those attending and organising events exchange views and express opinions indicative of how they are likely to behave. Across these platforms, as well as more obscure online noticeboards and forums on the surface, deep, and dark web, threats and risks are shaped by rapidly changing sentiment and emotion, with the potential for deliberate misinformation to incite actions that put the public at risk.

Any event may generate thousands of digital conversations before it takes place, requiring police analysts to monitor, detect trends, unusual activity, or significant changes in mood or topics under discussion that could pose potential risks to safety. Early detection gives police coordinating teams the opportunity to prepare appropriately and reduce the risk of escalation.

AI-powered SOCMINT gives police a big head-start

For many policing agencies, their approach to online intelligence gathering has not fully caught up to the scale and pace of these online conversations. As such, many lack the means to achieve this early warning, which is where AI-powered social-media intelligence (SOCMINT) technology fills the gap. It has been designed to analyse large volumes of social media content at high speed to high levels of accuracy.

It gives policing and security teams scalable, near-real-time data from digital conversations and online chatter on mainstream social media platforms, niche online channels and the forums run by activists, hooligans or violent extremist groups.

Police can configure this multi-lingual technology to pick up the sentiment changes that interest them and automatically detect indicators of illegal or disruptive activity and incitement to violence. Visualisations enable fast insight into links between individuals and groups across regional and national boundaries. Achieving this level of analysis is impossible manually within the resource constraints faced by police forces and allied agencies.

Insights aid proactive collaboration

While no single technology can address every risk ahead of each event, SOCMINT has a major role to play in putting police on the front foot when they are faced with ensuring public safety at major events. Whether it is organised for entertainment, lawful mass political protest, a commemoration or a rally, effective security comes from collaboration between police, event organisers and intelligence teams armed with credible and actionable insights.

Ensuring an event passes off without serious incident may simply require the alteration of certain arrangements relating to access, ticketing and physical security at the venue. In other cases, it may require the barring, or close surveillance of individuals known to be intent on causing trouble.

Final decisions about the seriousness of threats are always down to police officers using their experience and understanding of the wider context. But armed with real-time, AI-enabled online insights, senior officers can make better-informed decisions about pre-emptive action, permissions for the event, or how they allocate resources more effectively. If a disturbance occurs, they are better prepared, and responses are more likely to be proportionate.

With threats coming from so many sources, SOCMINT has the ability to bring the policing of events fully into the digital age to ensure the protection of the public and officers, and to achieve greater efficiency in resource allocation.

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