Minority Social Report

Hitachi announced this week that it has developed a powerful and robust new technology called ‘Hitachi Visualization Predictive Crime Analytics’ that has the ability to pinpoint when and where a crime will occur. It’s all about gathering data from a fire hose of multiple real-time sources and also social media conversations. The system then uses machine learning to find patterns that humans can’t see with the goal of making our cities safer places to live.

It’s mind blowing how the Hitachi Visualization Predictive Crime Analytics system can specify potential crime scenes down to a relatively small 200-square-meter spot, and it assigns relative threat levels to every situation. Traditionally, police investigators build crime-prediction models based on their experience with certain variables, such as the location of schools or slang words for drugs that pop up on Twitter. They assign a weight to each variable based on how important it seems to be. This is now streamlined with Hitachi’s system which doesn’t require a human to figure out what variables matter and how much. The main benefit of the system is to create rich actionable insights and threat level predictions that can accurately forecast both when and where crimes are most likely to happen and whether or not additional resources are likely to be needed in the area.

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Social media is often used in solving crimes: from soliciting crime tips, to identifying people and their locations, gathering evidence, and notifying the public, law enforcement has been using social media for some time. This also isn’t the first time social media has been used in prediction. Twitter has previously been used to predict flu epidemics and even predict the stock market. Traditionally, police investigators build crime-prediction models based on their experience with certain variables, such as the location of schools or slang words for drugs that pop up on Twitter. They assign a weight to each variable based on how important it seems to be. This is now streamlined with Hitachi’s system which doesn’t require a human to figure out what variables matter and how much. “You just feed those data sets,” says Mark Jules, Hitachi’s Public Safety and Visualization division “And it decides, over a couple of weeks, if there a correlation.” The main benefit of the system is to create rich actionable insights and threat level predictions that can accurately forecast both when and where crimes are most likely to happen and whether or not additional resources are likely to be needed in the area. As far as predicting crime goes, social media plays a big role and it can even improve accuracy by 15%.

Crime scene

Hitachi uses natural language processing: the ability of a computer to take in and understand colloquial text or speech. The system can sort through every single tweet tagged to a specific geography to find the most significant words that indicate what’s happening. Gangs, for instance, often use different keywords to meet up or coordinate activity.  While we may not know what that keyword is, the software can identify anything that’s abnormal, such as someone using an off-topic word, or using it in a very tight density or proximity, and then assign it a bigger weight in the results.

One thing social media indicates is tension between neighborhoods that could turn violent. “We were talking to [Washington] D.C., and they said, our biggest cause and effect is what neighborhood you’re closest to,” says Lipscomb. “There are these neighborhood rivalries going on in D.C.” “Normally”, said Jules, “police wouldn’t realize the correlation between neighborhood tension flare-ups and crime until months later.”

The company plans to put the system into a trial run at police departments in a handful of unspecified cities starting with some obvious concerns that I would be happy to describe you in some possible discussions on the topic.

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