Cognitive Engagement: The New Propaganda Part 2


So where were we?


Oh yes, we were discussing the relevance of social network analytics (SNA) to psychological operations/ military information support operations (MISO) as expounded upon by the Dep. of Defense, Joint Chiefs, and the Dep. of Army:

“Human networks are tied together by certain quantifiable links: working together, kinship, friendship, financial transactions, and countless others. Of particular importance to PSYOP personnel may be the publically and commercially available data from social media platforms.”

The average person has no idea how social network analytics (SNA) operate, and in this particular deficit of knowledge, users are also unaware of the security risks posed by the information they post to social media platforms and the like.

Recall the scene in The Dark Knight when Batman resorts to illegally hacking the cellular signal transmissions of every citizen in Gotham to create a real-time, multilayered visual of the city in order to find the Joker and his hostages. The result of SNA is sort of like this.

By collating, analyzing, and integrating enough data from commercial and public sources, one can create an elaborate ‘map’ of the flow and spread of information through social media. This map depicts informational profiles of users as well. With SNA, one can also use the resultant map to target certain information nodes to either stop information from spreading through a network or propagate MISO critical messages.

In this present Part 2 of Cognitive Engagement, I aim to supply a condensed run-down of SNA, along with the explanations of SNA from source documents in hopes of conveying the essence of a novel, obscure notion of data-mining relating to human freedom and the evolution of propaganda.

To begin, we must know what the metrics of SNU are.


SNU Metrics

The document cited in Part 1 of Cognitive Engagement details the metrics of SNU.

These metrics are:

  1. Centrality: a centrality measure is any metric used to determine a social media user’s preeminence/ sphere of influence within a network.
  2. Degree: a centrality measure of a social media user. The rule of ‘degree’ is basic – he/she with many social contacts, say “200”, has a greater degree of influence than one with 20.
  3. Eigenvector Centrality: a nuanced centrality metric that is used to determine how connected a social media user is with users possessing a high degree of influence. “This index locates actors who are the top of hierarchies or are popular within the network.”
  4. Betweeness Centrality: used to determine “nodes” or individuals in a network that are “uniquely” connected to other users in such a manner that resembles information access control. Without these “betweenness” nodes, certain information ‘contagions’ will not spread.
  5. Key Player Centrality: used to identify what individuals of a given network possess the highest overall influence. “MISO teams can identify a set of well-connected actors to maximize the potential impact of a message and spread it through a given network influencing a given number of nodes with minimal overlap. This algorithm can also be applied to determine which set of nodes, if removed, would fragment a network the most and damage its ability to spread information or other resources.”

In synergy with the above metrics, a comprehensive understanding of a network can be derived with “community-detection algorithms” (CDA) such as the Girvan-Newman algorithm which detects and identifies “sub-groups” of a given network. It is also “used to great effect to identify cleavages within groups, which are not easily recognized, even by those within the group themselves. PSYOP teams could use this method to increase identification of cleavages to better tailor messages and understand the topography of their intended audience.”

Utilizing these components, along with suitable information technology, it is possible to modulate, disseminate, or block critical information from spreading through a network. Understandably these analytics can be put to reasonably justified uses such as monitoring and deterring terrorist cells, but where things get dicey in relation to human freedom is the monitoring of potential extremists.


 Who is Targeted and Why

As explicitly stated in the document, targets of MISO influence include the broad category of ‘potential extremists’. As we covered in a former post, the criteria for classifying one as a terrorist is not exactly perfect and may serve to label individuals in order to justify the deployment of SNA unwarrantedly:

“As related by the American Civil Liberties Union (ACLU) Sec. 802 of the U.S. PATRIOT ACT provides for the justification of legal pressures against civilian populations who hold to ideologies counter to established U.S. policies. In other words, if you happen to detest and protest a certain policy of the U.S., that very action may be interpreted as a form of domestic terrorism and therefore individuals participant in such protests may be deemed ‘terrorists’.”


It should also be noted that certain components of an individual’s world-perspective (ideology) may falsely betray one as a ‘potential extremist’. For example, a DHS document conveys the sentiment that a belief in a conspiratorial ‘new world order’ is radical. This implies that free-thought may be under attack in our society (or already has been for years).



No. The belief in a new world order is not kooky and it should not serve as a metric in determining one’s susceptibility to radicalization.

To be Continued…















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