Russian Info Ops on FB and Twitter: Correlation with Violent Crime?
Background &
Premise
Russian Information Operations targeting US citizens ramped
up significantly in 2015 and even more so in 2016 leading up to the November
presidential election. Further, these operations have a vastly broader scope
than the presidential election alone—the operations are extensive and ongoing,
they seem to be largely successful (at least as evidenced by the rhetoric of
Russian sources who work or have worked for such efforts, and at least in
comparison to similar Russian efforts in Finland, Germany, and France), and
they target US domestic religious groups, social movements, state and local
governments, educational institutions, and more.
These operations are born out of a robust info ops
infrastructure with close ties to Russian oligarchs and government agencies. Most
operations, and the Russian agents and agencies sponsoring and orchestrating them,
were created with specific political goals in mind, such as:
·
Undermining the strength of US democracy and
civil institutions, and eroding public faith in them,
·
Weakening US reputation and credibility abroad,
·
Further dividing the US population over
contentious political issues,
·
Increasing violent and hate-based protests
(marches, secessionist movements, etc.) in the US.
For the purposes of this SNA, data will focus on these groups’
efforts to incite, whether directly or indirectly, violence in the US. Russian
info ops have been linked to white supremacist protests in Charlottesville and
elsewhere, violence between Black Lives Matter and police officers (on both
sides), armed secessionist marches in multiple states (most notably Texas),
armed protests on behalf of religious groups (such as Westboro Baptist Church),
and many other protests that were of a violent nature or that could quickly
have escalated into violence.
One of the chief avenues of influence through which Russian
agents influence US citizens is social media. US citizens frequently do not
realize they are communicating with Russian agents or are part of Russian
government funded and organized groups pretending to be US grassroots groups.
“Lit Review”/Other
Work in this Field
Just one example of the research being done in this space is
the
Hamilton 68 project,
which uses a variety of analytic tools (not SNA, but complementary analytics) to
examine the extent of Russian Influence Operations on Twitter (RIOT), named for
Alexander Hamilton’s 68
th essay of the
Federalist Papers, which has to do with foreign interference in US
elections. RAND has conducted extensive work on information operations, and
Foreign Policy has for months been
publishing multiple articles a week on Russian info ops in the US. SNA has
certainly been used by both US and Russian organizations in examining this
field, particularly in conjunction with SOF, though it is not open-source.
Research Question
The key research
question is: are Russian information operations on social media significantly
increasing the level of violent crime in the US?
Scope & Data
Gathering Methodology
Citizens convicted of most violent crimes in the US are
listed in public state databases. The SNA will be limited to FB and Twitter groups
sponsored by Russian government organizations between 2015 and 2017, and
Facebook and Twitter users who 1) were public members of these Facebook groups
or were following these Twitter groups with public, personal Twitter accounts,
and 2) who were subsequently convicted of violent crimes. This is publicly
available data—we first look up those convicted of a violent crime in the last
two years in a given state, and we subsequently run through the list of names
to see whether each was a member of / was following certain FB/Twitter groups.
In addition to areas of potential insight from the SNA,
elaborated on below, the fundamental answer to the research question will be answered
primarily by comparing rates of violent crime among individuals who were
followers of Russian influence operations with overall rates of violent crime
in various states. If US citizens actively following several Russian
agent-operated FB and Twitter groups are 2.4x more likely to be convicted of a
violent crime as citizens not actively following such groups, for instance, then
there is a clear correlation between these operations and the number of violent
crimes in the US.
To allow for a more manageable scope, other social media
platforms will not be included (though they are certainly relevant—see “Further
Analysis” below).
Further allowing for a more manageable scope, at least at
the advent of the project, the SNA will focus solely on groups that are
publicly known to be run by Russian agents (notably by the Russian Internet
Research Agency). The project will not examine all 3000+ FB ads that were
Russian-sponsored—in addition to numerical problems, it is too difficult to
determine who viewed particular ads, and FB does not disclose this data
publicly.
There are a number of potential flaws with the methodology.
First, the influence of info ops is not limited solely to violent crimes.
Second, most of those involved in extremist and/or hate-based movements in the
US are not subsequently convicted of violent crimes. Third, many of those
influenced by Russian operations are not actively following such groups, but
are influenced by intermediaries—friends, neighbors, coworkers. Fourth, though
not final, there are doubtless many FB/Twitter groups run by Russian info
operatives that we are not presently aware of. We are operating from a limited
pool for the purposes of this SNA. However, the analysis will still yield
important insights into the research question and perhaps into the larger field
of information operations.
Further Research
This project leaves substantial room for further analysis
that would likely provide compounding insights. In terms of initial analysis,
this SNA project would be best approached 1) by first looking at FB groups, and
second looking at Twitter operations; and 2) by working state-by-state through
databases listing individuals convicted of violent crimes. This is publicly
available information, though it varies state by state—some states, such as
Texas, list all individuals convicted of “Class B Misdemeanor” crimes and
above, while some state databases include individuals convicted of felonies
only, etc.
For further analysis, other social media platforms could be
included. The same day that FB shut down the FB group of the largest
secessionist movement in Texas, for instance, which was run directly by Russian
agents, the group moved to Instagram.
Additionally, the further analysis that might yield the
greatest insights would be to delve deeper into the connections between the Russian
influence operations and the extent to which US individuals were effectively
influenced. This would address a more qualitative, equally essential part of
the research question; SNA is just one important technique to get to the heart
of the problem.
SNA would be especially valuable in the beginning as a means
of demonstrating the magnitude of the problem both to policymakers and to the
targeted, influenced citizens themselves, particularly in an increasingly
“bubbled” society. Ultimately, further analysis might yield insights into the
methods and processes through which the Russian info operations infrastructure
works, and ways in which the US citizenship might be made more resilient to
such influence—particularly where such influence leads to greater violence.
Network Analysis
This project will create a two-mode SNA using FB and Twitter
groups sponsored by Russian government agents/agencies as one mode (“node type
1,” distinguishable by color) and specific individuals who were convicted of
violent crimes and who were members of or followers of these FB and Twitter
groups as the second mode (“node type 2”).
In the analysis, I will examine different levels of
dichotimization of how many Russian-sponsored FB/Twitter groups of which each
individual was a member. If available data is sufficient, and if macros provide
an effective tool to gather the data, I’d also like to code for and examine
different levels of dichotimization of how active each individual was in each
group (i.e. number of posts in a Facebook group, number of retweets of a
Russian agent’s post, etc.). This would create an additional, valued matrix for
my analysis.
Centrality measures and tie strength might prove useful for
analyzing which FB/Twitter groups were most influential, and the extent of
their reach. Some US citizens active on social media might, for instance, be
shown to have significantly extended the reach of such groups if they show a
high Betweenness between group creators and violent criminals—event organizers,
for instance. There might also be a correlation between those convicted of
violent crimes acting out of strong feeling towards a particular political
issue, and the number of FB/Twitter groups they were influenced by (Eigenvector
and Egonets are two ways of further examining this)—from this, one might argue
there is evidence of “stacking” influence. Centrality measures might also provide
insight into which contentious issues were most effectively manipulated into
violence—whether, for instance, followers of race-focused groups were more
likely to be subsequently convicted of violent crimes than followers of religion-
or secession-focused groups. Many other possible insights from tie strength and
various centrality measures are possible with further analysis.
Further insights would likely be gleaned from faction
analysis, particularly when analyzing the overall network by region. It might
be possible, for instance, that certain regions of the US were more prone to
influence escalating into violence than others. With sufficient data, faction
analysis might also show which Russian groups were most effective at inciting
violence among US social groups.
Attributes
Attributes that could be linked to specific nodes include:
Node Type 1:
·
The specific government or government-contracted
agency/corporation sponsoring political information operations targeting the US
public.
o
If publicly available data is sufficient,
research might allow for two distinct attributes- one for sponsorship, in terms
of funding, political endorsement/authorization, and logistical support, and
another for orchestration, referring to the agents actually authoring and posting
in such social media groups, pretending to be US citizens with divisive
opinions, etc. (operating a level below the individual/institutional sponsors).
o
Again, if publicly available information proves
sufficient, these attributes might be further subdivided by the ties or types
of ties that info op sponsorship institutions have to high level Russian
politicians, oligarchs, and other power brokers (President Putin, members of
the Politburo, billionaires). Further SNA analysis is required before these
ties and types can be effectively categorized.
·
Attributes corresponding with a particular US
region or particular, divisive US political issue.
·
For further analysis, broadening the scope: Social
media groups and activity limited specifically to influencing US opinion; to
influencing Russian opinion; to influencing opinion (and available information,
and upsetting the veracity of available information) in other countries towards
the US and/or towards Russia; and any overlap/interrelation.
Node Type 2:
·
Type of violent crime of which the individual
was convicted, and crucially—requiring further research and analysis—whether
the crime was motivated by hatred towards specific groups of a diametrically
opposed political stance. E.g. violent protests by white supremacists
influenced by Russian propaganda designed specifically to promote hatred
towards blacks, or towards immigrants; lone wolf attacks against police
officers by citizens who were members of Russian-operated groups that promoted
violence against law enforcement; etc.
·
Whether the individual followed Twitter groups
or Facebook groups, or both.