DARPA’s two-year old program to better understand and perhaps ultimately influence social media has begun to bear fruit but some of that harvest is raising a stink.
DARPA said when rolling out its Social Media in Strategic Communication (SMISC) program its goal was to develop a social networks science and create automated and operator support tools and techniques for the systematic use of social media at data scale.
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In building that science the agency says it has funded myriad social media/Twitter research (including a study that looked at Lady Gaga’s Twitter following—a model of social media popularity, DARPA stated) as well as a look into Facebook, Twitter, Pinterest, Reddit and Kickstarter. Perhaps if the recent reports of FaceBook actually manipulating the feelings of its users in a 2012 experiment, the work DARPA has been doing would not have raised as many eyebrows.
DARPA today issued more information about the SMISC and directly commented on the FaceBook controversy stating: “DARPA does not support research programs that aim to deceive unwitting people to see how they react (as the controversial Facebook study did). DARPA funds research on how groups form and influence each other and related dynamics – similar to social science research that has been conducted for decades with other kinds of communication.”
ReutersDARPA went on to say that “SMISC will focus research on linguistic cues, patterns of information flow and detection of sentiment or opinion in information generated and spread through social media. Researchers will also attempt to track ideas and concepts to analyze patterns and cultural narratives. If successful, they should be able to model emergent communities and analyze narratives and their participants, as well as characterize generation of automated content, such as by bots, in social media and crowd sourcing.”
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DARPA has kept its research as secret either by publishing its work on its website.
From DARPA: "Events in social media space involve many‐to‐many interactions among numbers of people at a compressed scale of time that is unprecedented. Entirely new phenomena are emerging that require thinking about social interactions in a new way. The tools that we have today for awareness and defense in the social media space are heavily dependent on chance. We must eliminate our current reliance on a combination of luck and unsophisticated manual methods by using systematic automated and semi‐automated human operator support to detect, classify, measure, track and influence events in social media at data scale."
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