Monday, February 11, 2013

Raytheon RIOT- an analytic social media tool

Raytheon, the world's fifth largest defense contractor, has developed a software tool that can track and predict people's behavioral movements by mining data from social networking websites such as Facebook and Twitter. According to this article from the Guardian UK news source, the 'extreme-scale analytics system' named RIOT (Rapid Information Overlay Technology) was developed in coordination with the US government to help build a national security system that can serve as surveillance to track a person's whereabouts.
The way RIOT can determine a person's whereabouts is by using relationships between people and their social media accounts to create association rules that can be displayed by a spider diagram. In using the RIOT interface, a search for a particular person can return several functions created by these association rules. For example, the function 'getLocations' returns a Google Earth link that pinpoints all of the "locations" a person had checked into on Foursquare or that had been stripped from the longitude and latitude data in the photos on Facebook that were tagged with or on a person's profile. Furthermore, the function 'getPlaces' returns the top 10 places that a person checks into and also allows one to analyze what the most frequent time of month, day, and hour a person visits those locations. In the example highlighted in the video, RIOT determined that the best way to get a hold of 'Nick' is to visit him at 6 am at the gym on a Monday.
While the video offered a simplistic example of how RIOT could be implemented, Raytheon featured RIOT in a patent that it is pursuing to 'gather data on people from these social networks to identify whether or not they should be judged a security risk'. Furthermore, company spokesman Jared Adams states that they are working with various industrial partners to help turn 'massive amounts of data into usable information to help meet our nation's rapidly changing security needs' while 'enabling the sharing and analysis of data without personally identifiable information [such as social security numbers, bank or other financial account information] being disclosed'.
I think that successful implementation of this program can aid in determining people's routines in order to create more efficient products and resources. For example, if I was rushing to work after my morning gym workout at 6 am on a Monday, a restaurant on my way to my office may consider offering breakfast. This could also prove to be useful in real estate; property values can be adjusted based on traffic modeling of an area using location data mined in RIOT. Finally, this program can be used by municipalities in order to create a supportive infrastructure for roadways and utility companies if residents are predicted to be traveling in certain patterns or certain time frames.


  1. RIOT could save tax dollars, as well as make it easier for police to chase down bad guys and help government officials stop terrorist attacks. On the other hand, the price could be the loss of individual privacy. This no doubt will raise hackles about an ominous-sounding breach of privacy on the horizon.
    As mentioned in the parent article ‘The Rapid Information Overly Technology’ reportedly can track check-in posts and geo tagged photos in social media. Further, it can chart social connections and highlight those an individual communicates with most often. This also develops a visualization model which shows a predictive animation module on how an individual’s life can be mapped. It ultimately undermines any privacy manners. It is also possible that the potential benefits to law enforcement are overrated.
    ‘Evil-doers’ already know about the software's existence and can easily avoid being tracked via social networks, or even leave a false trail. In other words, if criminal masterminds know that this technology exists, they can just establish a misleading routine to throw off pursuers when they make their actual strike. Meanwhile, members of the population as a whole could be ignorant of the technology and fail to take necessary steps to protect themselves. However this form of technology is not relatively new as ‘spying’ projects, reconstruction events have been successfully implemented in the past. What makes this technology innovative are the sources of data mining, technological advent of open source software and predominant growth of social media which makes access to datasets relatively easy.

  2. I agree with you. Thank you for sharing the update. It is interesting to have it discussed widely so that we can gain more objective opinions.

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