Sunday Times 2
Fast, on-the-ground military intelligence gleaned from social media, thanks to AI
View(s):By Shanika Karunasekera
In times of disaster, military attack, mass uprising and political unrest, social media sites such as Twitter, Facebook and even Reddit can contain vital information from on-ground witnesses worldwide.
Crowdsourced information from social media can include critical details that enhance military intelligence, improving responders’ decision-making and potentially saving lives; but it is challenging to uncover these details from the high data volumes generated under swiftly changing security threat situations.
The Real-time Analytics Platform for Interactive Data-mining (RAPID) platform consumes fast-moving data streams to deliver analysis in real-time. Picture: University of Melbourne
Where human processing of information would be too slow to guide a response to developing situations, artificial intelligence can help. Australia’s Defence Science and Technology Group (DSTG) and the University of Melbourne have developed an artificial intelligence-led platform designed to gather and analyse key intelligence sourced from social media sites.
Whether it’s information about an emergency like a bushfire, a political protest or military action such as missile strikes in Ukraine, important information is typically shared via the internet by people who are in the area at the time.
Professor Shanika Karunasekera
The Real-time Analytics Platform for Interactive Data-mining (RAPID) platform can consume fast-moving data streams and deliver analysis in real time, such as visualisations that cluster networks of tweets, users, keywords and topics, and deep dives into discussions on particular topics or between persons of interest, quickly zeroing in on significant data. Purpose-designed techniques, paradigms and algorithms are used to analyse a large amount of data in real time.
Work on the RAPID platform started nearly a decade ago, as a collaboration between University of Melbourne mathematicians and social scientists. The work tapped into the social scientists’ extensive expertise in mapping physical, real-world social networks to build mathematical models that could better analyse and predict these relationships.
The researchers built on this work in the ensuing years to cater for the massive growth in data, as social media sites generated millions of posts hour by hour.
The team at the School of Computing and Information Systems in the University of Melbourne’s Faculty of Engineering and Information Technology has since further developed their mathematical models of social networks so that when applied to fast-moving data such as posts on sites like Twitter or Reddit, they can reveal patterns that might otherwise be invisible. Developments involved filtering the essential information from a big, noisy dataset to formally construct networks in a way that would help the team analyse them.
Big data’s potential for defence applications has been appreciated for some time. Following 9/11, there was a global push for agencies to assess terrorism activities in a different way. There was growing recognition that tracking and monitoring criminal and terrorist networks could both deter and prevent attacks. Agencies were interested in understanding the significance of these covert networks.
Warfare is no longer focused purely on military hardware – democracies are increasingly being threatened by a misinformation war, where fear campaigns are used to incite discord and radicalise individuals.
RAPID can adopt different decision-support scenarios to compare and time-sequence events and can push data to downstream systems for more secure analysis.
In military scenarios, where effective decisions rely on comprehensive and trustworthy information, the RAPID platform can deliver timely analysis in a fast-moving situation.
(Professor Shanika Karunasekera is Deputy Dean (academic), Faculty of Engineering and Information Technology, University of Melbourne.)
Courtesy The Australian