Thanks so much for coming today. I am Dr. Caroline Orabueno. I'm a postdoctoral research
associate at the University of Maryland's Applied Research Laboratory for Intelligence and Security,
and I will be presenting today along with my colleague Rainer Washburn, who is also at the
University of Maryland in our START program. We're very excited to talk to you today about a topic
that has taken center stage since 2016, and particularly during the coronavirus pandemic,
and that topic is the information environment, and specifically the role of supply and demand
factors. First, I'll start out by introducing the concept of data deficits, which arise when
the supply of credible information can't keep up with the demand for it, which creates an
information environment that can be easily exploited.
As we've seen throughout the pandemic, crises are breeding grounds for mis- and disinformation,
and data deficits exploit that vulnerability. However, by studying data deficits, we can
expose hidden patterns and reveal insights to help us better understand our information environment
and address the vulnerabilities that leave us open to manipulation, deception, and other forms
of malign influence. In today's discussion, we hope to present a conceptualization of data deficits
as an attempt to address the fundamental challenges of our era, the challenges of mitigating
information-based harms while maintaining an open and free information space.
Thank you for joining us, and here's my colleague Rainer Washburn to walk us through the agenda, and
then later to speak to us about some of the research he's done as part of an internal research and
development project at the Applied Research Laboratory program.
for Intelligence and Security at the University of Maryland.
Thank you, Caroline.
Hi, this is Rainer Washburn.
Again, thank you.
Echoing what Dr.
Orr said, appreciate here to be able to present with you today.
And so for our agenda,
what Dr.
Orr will be presenting on are what are data deficits?
When do they appear?
How do we detect them?
Also, along with examples of data deficits, including the COVID vaccine
misinformation, such as narratives and tactics,
and then wrapping up by looking ahead past COVID,
where I will go into my part of the research,
which we look at in Central Asia, specifically Kazakhstan,
namely the media landscape, how data deficits and data voids are formed
and why the individuals and whole populations migrate to our areas
that form disinformation, such as a telegram ecosystem.
We'll be looking at elements of influence.
So the tactics and techniques that we did observe
in the telegramming ecosystem.
And then we'll also provide a strategic observational note,
which I hope everyone will find interesting along with the rest of our presentation.
So without further ado, I'd like to turn it back over to my colleague,
Dr. Orr, for her part of the presentation.
Thank you.
So a few weeks ago on Twitter,
a user pointed out that Googling the search term
desk ornament returned some unexpected results.
Specifically, if you looked at the images in the Google search results,
you would have seen photo after photo of Nazi memorabilia.
The incident mirrored a previous controversy when searching the phrase
Jewish baby stroller on Google returned images of portable ovens,
a clear example of what we call portable ovens.
And if you looked at the image you saw in the Google search results,
And what exactly is driving these troubling search trends?
Well, they're the result of something called a data void,
which describes the situation in which search engine queries return little or no relevant information.
We've seen these pop up around disinformation narratives related to a variety of topics,
ranging from extremism to the coronavirus pandemic to Russia's war in Ukraine.
And today we're going to talk about one type of data void, which is the ability to see the data.
void called a data deficit and explore how this phenomenon interacts with other features of the
information environment to create conditions that are conducive to misinformation and vulnerable to
exploitation by bad actors although data deficits are the product of a lack of credible information
they can also be exacerbated by the overabundance of irrelevant and low credibility information
which can create the illusion that there's a sufficient supply of information when in fact
that information isn't meeting the needs of those demanding it and that's what creates this data
deficit moving along and looking at why and when data deficits emerge there are certain conditions
that are very conducive to this phenomenon specifically when supply fails to keep up with
demand and when supply fails to keep up with demand
when we talk about supply here we're talking about more than just the amount of information
available we're also talking about whether that information is discoverable readable
interpretable whether it's relevant and whether it's credible simply having information out there
is not enough if no one is seeing it or if nobody can understand it or if nobody finds it relevant
this often occurs data deficits often occur when interest in a topic is new
and on the rise so you often see it during periods of movement
and changes in interest and search queries these may be temporary they actually often
are temporary and transient but they can also persist for long periods of time
the nature of data deficits is such that they can often only be discovered through searching for very
specific keywords so if you're not searching for those keywords
you're not going to be aware that these data deficits even exist which makes them particularly
pernicious because they can exist out there in darkness for a long time without anybody even
being aware that they're there they often occur organically they arise again often just as a
product of these supply and demand features but they can also be the result of deliberate
manipulation and that's often the case as well
often the case looking at disinformation narratives surrounding extremism that they often
are the result of deliberate campaigns and deliberate efforts to funnel people into
certain content often for the purpose of radicalization
low supply specifically occurs where incredible information either isn't available or doesn't
exist at all so that's a condition where
people are showing interest in something or or um searching for something that simply there isn't
information about um when when that information isn't discoverable or isn't reaching people so
it's out there but it's just not getting to people for some reason or it's in progress or still
unfolding and this was a big thing during the coronavirus pandemic because we were still seeing
studies underway evidence was was not certain you know it was a big thing during the coronavirus
pandemic but the information is coming to us and it's not enough yeah um yeah it's the nature of
science but in these conditions it creates a problem uh when providers of disinformation
are producing uh content regularly and presenting it as certain and uh on the other end of things
that information just is is not available to um to match that um moving along
again
again, these moments of vulnerability.
So we looked last at sort of the features
that set the conditions for data deficits.
And there are certain moments of vulnerability
that make us particularly susceptible,
make our information environment particularly susceptible.
One of those conditions is crisis events.
Again, the coronavirus pandemic
is a perfect example of that.
Crisis events have a lot of features about them
that make our information environment
and the people operating in it particularly susceptible
to all sorts of deception, manipulation, disinformation.
Some of these features include things like uncertainty, fear.
We're all having a shared experience
and wanting to understand it,
wanting to make sense of what's going on.
We engage in something,
something called collective sense-making.
And part of that process involves information seeking.
But that sense-making process
can also quickly become conspiracy theorizing.
We saw that happen over and over again during the pandemic.
And it can also just result in sort of a unscientific
and unstructured process of people sharing ideas,
which is not inherently bad.
But when those ideas clog out the scientific information
that's needed to protect yourself from a deadly pandemic,
that's when it becomes a bad thing.
And that's where the overabundance of information
becomes a problem in and of itself,
when that information crowds out
the potentially life-saving information
that people are trying to find.
Another moment of vulnerability are breaking news events.
This could be mass shootings are a prime example of this
because they're often followed by quite harmful data deficits
that can be exploited in extremely harmful ways.
And the reason this is a moment of vulnerability
is because of that rapid surge
in interest and information seeking,
and just the complete inability to match
that rapid increase in interest with a problem,
proper supply of credible information um and another moment of vulnerability is um when when
bad actors purposefully manipulate search trends and um a good place to see some examples of this
would be 4chan in the aftermath of a mass shooting uh moving right along
and how do we detect data deficits so how do we find these how do we look for them
um there are a variety of tools and techniques there's no one way to do it uh and there are
actually some really cool things being developed and that have been developed during the pandemic
uh to look at these to look at data deficits and and start to um have reliable and and validated
ways to measure them um some of the tools and techniques that i have personally used and i've
done a fair bit of of work in this area and i've done a fair bit of work in this area and i've
done a fair bit of work in this area i haven't always labeled uh the this phenomenon as as a
data deficit that was a term that um a microsoft researcher came up with in in 2018 and um since
then it's kind of been reformulated by uh data and society uh first draft news they've all
contributed to uh the current conceptualization of what a data deficit is in my own research some of
the the tools and techniques that i have used um include real-time monitoring of trends that's one
of the um big opportunities uh in researching data deficits is it is real time and it gives you the
opportunity to actually detect and potentially prevent uh information-based harms before they
before they harm anyone um and real-time monitoring can include things like monitoring
google trends trending topics and hashtags
to look at the demand side um looking at things like the number of fact checks and and the
characteristics of fact checks that are out there um looking at trends in scientific publications
um using media monitoring tools all of those would be looking at the supply side of things
also long-term studies of trends in the information ecosystem so i'm i'm a proponent
here of mixed methods research i think
um there's some some really cool ways here to track narratives and to really look at
over time you know what does it look like what do people uh what kinds of search terms are people
using you know in the aftermath of a mass shooting or what kinds of search terms do people use when
we have a terrorist attack or um when there's a new emerging infectious disease and understanding
these things and starting to to be able to identify patterns can help us
to understand what's happening in a platform and to now have a approach to sort of
information them because then we can really also know what events are going on and how
learn more about data and then when it happens again to be prepared for it and to know sort of
what it looks like when i when a data deficit is forming and what it looks like you know when
when conspiracy theories are forming.
So it gives us sort of a signal
that we can use in the future then to get ahead of it.
And then another technique that I know
I'm not the only researcher in this area who does this,
but sort of targeted monitoring
of common disinformation origin sites.
Again, 4chan is a big one.
Whenever there's a terror attack or a mass shooting,
you go to 4chan, there's a good chance
you can identify some disinformation campaigns
and likely data deficits before they emerge.
Moving along, looking specifically this time at social media.
So when we're talking about data deficits,
they can arise on social media,
they can arise on search platforms.
They're not specific to any platform,
but looking at how we detect them on social media
and what kind of tools
and techniques are available.
And again, there are tons more
than what I'm getting into here.
These are just some of the tools and techniques
that I personally find most helpful and promising.
Engagement metrics, it sounds very simple and it sort of is,
but sometimes credible information exists,
but again, no one's seeing it or engaging with it.
And that creates a data deficit.
Even if the information is out there, you know,
people have to see it and if they're not seeing it then the demand isn't being met by the supply
so when interest in a topic or keyword is high but engagement in related posts or tweets is low
this may indicate a data deficit and an example of that from a study i did a few years ago
looking at uh posts about ebola on instagram and twitter by um three leading health organizations
the world health organization cdc and doctors without borders um and looking at how they
addressed uh ebola related risks on on social media we found um basically number one that
these major health organizations were largely absent in spaces
where misinformation was present they it wasn't that they were ignoring the issue of
misinformation but they weren't going to the places where the misinformation was and of course
that means that the people who were in those spaces weren't seeing the information from the
credible sources um we found that these health organizations weren't also weren't fully
utilizing image-based platforms and this is an important finding because they're still not fully
utilizing a lot of what i would sort of call alternative social
media platforms so you know reiner's going to talk to us about telegram
that's one that a lot of health organizations and scientific organizations are completely absent from
there's no presence whatsoever and it just creates this very again a large vacuum that is
going to be filled by someone and unfortunately we often see it filled by bad actors as a result
all three of these health organizations were posting fact checks and posting relevant information
but the engagement
with those posts was extremely low so again that gets back to exactly what i
i just mentioned at the beginning of this slide that's an indicator of the data deficit
when in the middle of the ebola uh epidemic of 2014 to 2016 when interest and fear were sky high
people wanted to read about it people wanted information about it they were putting it out
there but nobody was engaging with it so something is off there and again
this is something that i think is really important and i think it's really important for us to
think about it and i think it's really important for us to think about how we interpret that as a
sign of a data deficit this information for some reason was not reaching people and one of the
reasons was that that content wasn't designed to be shared um the content they were putting out
was sort of what what these health organizations thought was important but that's not necessarily
the same thing that the public thinks is important um and this allowed for a data deficit to form
and i think this is a really important tool for us to think about um so um just another example
of um a tool to detect data deficits and this is a tool that um i again i have used and think it's
it's quite uh quite a cool uh development during the again this was developed during the coronavirus
pandemic um these uh researchers developed a taxonomy to look at global public conversations
related to cover 19 they basically came up with five categories of coronavirus discussions and
35 subcategories um and then they they used uh they used these categories to aggregate data
on a weekly basis they looked at things like volume and velocity and the presence of questions
basically to detect signals of information voids and data deficits and areas with potential for
confusion or where misinformation is
and disinformation may thrive um and they use that as sort of an early warning
uh system and created if i i would highly recommend checking this out um
this toolbox i put the link in this slide um and you can go you can create a dashboard you can do
your own tracking you can look by country you can look um by by date by volume and basically create
your own system to monitor this little piece of the coronavirus uh infodemic as they're calling it
um and it kind of gives you an idea of how it can be done in other areas too and that's
that's one of the things that um i hope you'll take away from this today is that you know a lot
of this has been developed in response to covid but there are applications of this to a ton of
other topics um and i think they're going to be a great tool for that um and then also i'm going to
also highlight that the uh uh the use of the data as a tool is really important and i think this
is a really important tool for some really promising avenues um moving ahead so next
moving to the next slide um again specifically about covid um some of the again i have used
some of these tools to track um various narratives data deficits um ex exploited um exploited data
deficits conspiracy theories and some of the key vaccine related narratives are um you know these
narratives where I was able to find identifiable data deficits, included narratives around things
like the claim that natural immunity is better than, that natural immunity through diet and
exercise is better than getting vaccinated. And if you look, I kind of put a little note by the
side of it, how the data deficit was created. So in this case, the credible information wasn't
available or discoverable and wasn't reaching people. In the case of this claim that vaccines
would sort of be this golden ticket out of the pandemic, that was created by supply problems
from still emerging evidence. So the evidence wasn't certain. The disinformation purveyors
were putting out tons and the credible sources couldn't answer it. I did a small project on
the FDA.
The FDA's approval, disinformation narrative surrounding the FDA's approval of the Pfizer vaccine
and a subsequent FOIA request that in that case, the problem was really created by this huge lag
time where this disinformation narrative got set. And the credible information to answer it didn't
come out for a full month. And even then, the information was not in such a way, was not
presented in such a way that it would be able to answer it. So I think that's a really good
example of how the data deficit was created in such a way that it was interpretable or
readable by most of the general public.
And just another example that's not vaccine related, but it's very much COVID related,
is the lab leak versus zoonotic origins theory. And the supply problems that created this
data deficit included flag time, and of course, still emerging evidence, which we are still
seeing issues with today.
And moving to the next slide.
Okay.
So related, this is sort of the second piece of this, the last slide. So the last slide looked at
the key narratives. These are the key tactics that were used to exploit those data deficits in order
to promote those misleading narratives.
So these tactics included things like capitalizing on keywords around specific vaccines, specific
vaccine ingredients.
Or alleged ingredients, side effects or alleged side effects, and other very specific keyword
sensitive topics.
And that's kind of the important piece here is the very, they're keyword sensitive topics.
Laundering old and pre-existing conspiratorial narratives.
So kind of taking something that was already there that people might be familiar with and
repackaging it in the context of the COVID vaccine.
Okay.
Document dumps.
Again, going back to that FOIA request around the Pfizer approval by the FDA.
Often, these conspiratorial narratives will involve the release of large data sets or
large dumps of documents.
And these documents are often disseminated very rapidly, and in order to properly analyze
them and actually present factual, reliable information, it takes time.
And unfortunately, in the time that credible sources are doing that work, the lower credibility
sources are pumping out information, you know, sometimes on an hourly basis.
And so a lot of bad information gets out there.
False misleading deceptive narratives take hold, and by the time the credible information
gets out there.
Okay.
The other narratives have already taken hold, and it, you know, once they have taken hold,
it's very hard to disrupt that.
So the document dumps using these deeply interconnected networks.
The anti-vax community on social media is extremely large and extremely interconnected,
and they sort of all play different roles, working together to co-create, spread, and
amplify, launder, and legitimize.
Narratives, conspiracy theories, and other forms of anti-vaccine myths and disinformation,
the use of copycat websites and fake scientific articles to bolster the legitimacy of content
and boost search result rankings, and the use of emotionally-laden images and videos,
which is always a favorite of disinformation campaigns.
And closing this out, looking beyond COVID.
So we've talked a lot about COVID.
We've talked a lot about the COVID vaccine, but looking at where else we can apply this
data deficit model, which again, I think it has some really promising potential, and
some of the promise in this lies in the way it encourages sort of a reconceptualization
of how we think of mis- and disinformation.
Right now, we tend to think of it as a static concept, as, you know, identifying misinformation.
Right?
That is just out there, just sitting out there waiting for us to find it.
When in reality, as I think you've seen, you know, through these slides and possibly
through your own work, you know, mis- and disinformation and online manipulation and
influence are dynamic.
They're not static.
They're not just sitting out there waiting for us to find them.
They're constantly changing.
They're personalized.
They appeal to certain segments of the population.
They may be there one day and not the next, or they may not be there today and then they're
there tomorrow.
So, it really does require, you know, a constant monitoring, and I think if we are still looking
at mis- and disinformation as static concepts, it's really going to be impossible for us
to properly address it because they're not.
They're dynamic, they're changing, and we need, you know, we need the tools and techniques
that address that.
This data deficit model also encourages us.
It's to take an audience-centered approach.
So we're talking about monitoring what people are actually talking about and asking questions
about and expressing concerns about, not just what, you know, fact checkers or reporters
or researchers think is important, but what the public thinks is important.
And that gets back to that study that I talked about with Ebola.
You know, it's not just what the World Health Organization thinks you should know, but what
does the public, you know, what do they want to know?
What do they think is important?
If we're not addressing that.
That's somebody else is going to.
And then also recognizing that mis- and disinformation are really inherent properties of our information
environment.
They're not foreign substances.
They're not being injected and, you know, sneaking in there.
They are a product of the platforms and the tools and the people who exist in our information
environment.
They are native to our information environment.
And we can't, you know, we can't fact check them away.
We can't label them away.
And we can't use content moderation to make them disappear.
We have to come up with solutions that involve changing the conditions of our information
environment that make it so conducive to mis- and disinformation.
And so for the next piece of this discussion, I'm going to turn it back over to my colleague
Reiner Washburn.
He's going to talk to us about how the phenomenon of data is so important.
He's going to talk about how data deficits fits into the bigger information landscape
alongside other tactics of disinformation, influence, and deception.
Thank you, Caroline.
That was a great intro and great presentation.
So carrying on where she left off, we're going to look at it from an on-the-ground
perspective.
And in this case, as is titled for our talk about analysis in Central Asia, we're going
to be looking specifically at Kazakhstan.
And just to keep some info points here.
We chose Kazakhstan mainly because it represents such a large portion of the information landscape
generated in Central Asia, on top of which of its unique position geopolitically, especially
between two major players in influence and information operations, the People's Republic
of China and the Russian Federation.
And so Kazakhstan plays a central part of this analysis.
And so when we look at.
Kazakhstan, we first have to look at, and when we're trying to get into data deficits
and the landscape of disinformation, we have to look at the media landscape.
And so when we went into looking at Kazakhstan, we compiled through using SEO tools like Alexa
Global Engagement, Internet Engagement Ranking Standard, which is defunct as of this May,
and the SEMrush product tools, we were able to look at what were the top sites that those
in Kazakhstan use, but just in general.
From that.
We were able to winnow down the news sites that were most frequented, and this included
sites like New York KZ, Sputnik, which a lot of folks are probably familiar with, the Information
Bureau, which is more popular in Central Asia, but also Eastern Europe, KazInform,
and very specific to southern Kazakhstan is Tengri News.
And of these areas, of these news sites, we were looking at what the concentration of
news was.
Especially in the midst of the pandemic.
And we were looking around between January of 2021 into December 2021.
And from there, we noticed a large concentration on news generated around COVID-19, vaccine
rollout within the country, and specifically also the concern of mis- and disinformation
that was being generated.
And what was most fascinating is that a lot of these sites were not...
Informing the public on news with regards to vaccines outside of Kazakhstan, but more
about what is just going on with COVID within the borders.
It wasn't necessarily talking about global efforts and anything.
So that presented a unique find, in my opinion, on what information is actually being presented
in an official fashion on a news site in the country, and what are people doing for more
information?
What are people doing for more information if the information they're seeking does not
exist?
So when we ran against sort of a wall with regards to how much information we were gleaning
from the news sites, we moved towards Telegram, which serves both as the number one in a sense
social media platform, but even though it's not technically social media.
But it's also, again, is the term most people are familiar with, like a town square for
many communities in Central Asia.
It's a great way for them to...
To find news, discussion points, and rally around issues that are of concern.
And again, on all of these sites that we saw, all of them had official Telegram channels,
and we were able to link into those channels, and then we were able to develop a way to
insert the anti-vaccination lexicon to see if any of their platforms in Telegram...
Any of their channels in Telegram were sharing content from possible misinformation.
Sites, or so forth.
And so when we did that, we did actually...
Were able to search and pivot and log many channels, Telegram channels, that promoted
anti-vax and COVID skepticism.
And of that, we were able to identify and monitor roughly 22 channels and groups, which,
I mean, again, if we had more time, we would love to have gone further.
But that is a significant find, considering the scope of our research project.
So...
In the media landscape...
We were seeing a dearth of information about the global pandemic, just what was mostly
only local.
And then furthermore, we were able to pivot into Telegram, which was sort of...
It is this town square for information to be...
For the public to consume on.
But it also moves people into areas of disinformation, into the fringe, and where...
And this is where Telegram as a platform thrives as a space for disinformation to grow.
So when we are looking at the Telegram ecosystem, as you can see...
These are the avatars that we pulled out and just trying to give you an understanding
of, like, there are quite a few out there.
And these are a mix of both Kazakh-speaking and Russian-speaking channels that we're able
to identify.
And in particular, through this, in the Telegram ecosystem, we were able to identify what we
call elements of influence, or another more official term is operations in the information
environment.
Right?
So in particular, how we mapped it out from what we were seeing, there were two kind
of core tactics, right?
From what we were looking at the operational...
At the operator perspective, so on the red side.
The network development function, or tactic, and the content creation.
And so under network development, what we notice is that it is the foundation for how
they...
How information operations are influenced is established.
And the core techniques covered through this...
This network development is being able to stand up or link to a narrative infrastructure,
so other websites, again, copycat websites, as Caroline mentioned earlier.
Social media pages and so forth.
But also cultivating and manufacturing SMEs, so subject matter experts, sock puppet accounts
and so forth, and influencers into being witting and unwitting agents.
And an additional technique which we will not be able to cover in this presentation
was how...
How the operators themselves obfuscated their ability, obfuscated themselves from
being tracked further.
But if anyone would like to learn more, I'd be more than happy to discuss that in greater
detail offline.
And content creation, which is the other tactic we observed, this is mostly about the implementation
of implementing concurrently or immediately after network development.
And the true aim of it is to target the population of the operation with...
So they can...
Get the target population to generate their own content, to make it organic so that it's
self-sustaining of the narrative.
So that way, the operator doesn't necessarily have to constantly put up guardrails and guide
the target.
The target then is able to self-sustain.
And we have seen that in multiple instances, both in the United States and Western Europe
and elsewhere.
And so this is not just unique to Kazakhstan or in the telegram space, but it is a global
phenomenon.
And so the core techniques covered here are the amplification of the conspiracy theories
by their agents, so winning and unwitting agents, and also providing or dropping evidence.
But there's also an additional technique, which again, we won't be able to cover, but
it is where we solve the distortion of reality through what we call IMEGs, images, memes,
emojis, and GIFs.
It's a very interesting piece.
Again, if you would like to talk more about it offline, I'd be more than happy to.
So IMEGs, images, memes, emojis, and GIFs.
So under network development, while we were looking through telegram and through this
tactic, the goal is to attract and sustain target population engagement.
So this is through when you're creating websites, social media groups, and pages, but also
connecting to the existing infrastructure developed by unaffiliated entities, so that
it engages with the target narrative.
And so in this area, what we can see is that scope and duration does greatly influence
the scale of the narrative infrastructure.
So that's a good example.
Last question.
I have a question that I'm sure a lot of people do, but it's a big question in their
minds too.
Because I'm sure that most of us are aware of it.
But if you look for it in China, I mean, it doesn't really happen if you don't have
Well, then it's not exactly an issue to to really look at it just because it's a
I think a lot of the things we're seeing, especially in China, is when you have a
Yeah, because you're not thinking about, say, how do I get this?
How do I do this?
Very interesting.
to this development and network development of the creating of the network infrastructure is linkage
to the other infrastructure so that again it can minimize resource commitments cost and preventing
operational security breaches because this allows the operator to minimize how much exposure they
have which then feeds into the tactic which we won't go over of you know office getting
the operator so and then in doing so and through this uh research that we looked at on telegram
we did discover a number of links to disinformation websites as i mentioned and so what was most
telling is that of here we saw not just telegram as the hub but you know we had to look at it as
there were many spokes involved so and ones that are most familiar to us are like instagram twitter
uh youtube was in very particular uh involved but also medium so traditional blog posts and sites
where people could do long form written essays and so forth and that was shared extensively
so the other technique under network development oh sorry uh the other development here is this is
an example of what we saw and this was a uh ukrainian website uh which was called fag
pandemic and you know unfortunately we're not able to give a full investigative uh look over
for this but we did note some aspects that this site was not generated in ukraine but
it was generated in russia and this was shared extensively across at least half a dozen um
of the pen of the telegram channels that we were monitoring so this is just one example of those
fake sites of narrative infrastructure that either the operators developed or they latched onto for
linkage so the other technique in network development is to create or co-opt agents
both winning and unwitting so here operators do set out to cultivate and recruit these agents
being winning or unwitting and the three most common agents at least from what we noticed here
are traditional celebrities so actors musicians athletes um social media influencers and then
try to true the subject matter experts so to speak now in the in the case of the first two agents so
traditional celebrities and social media influencers these two types of agents were
especially useful for boosterism you know having developing the repetition of the narrative and
again they don't have to be an expert on it they just have to be able to help lend the credibility
to the media and the user and instead of just promoting it themselves repeatedly and boosting
and boosting it up that's why we call it boosterism whereas smees are most valuable for narrative
laundering so they will publish articles they will appear in media both online in fringe and
in some cases uh they will move into more traditional media outlets more credible outlets
um and so that's what we noticed especially with the smees and narrative laundering where uh we saw
a couple of them moving not from just a page on media but to reputable credible websites and news
agencies in eastern europe so and this is not just a tactic we have seen here but elsewhere and again
if some people in the audience are probably most familiar with in secondary infection which was
presented by grafica a few years ago so in our case we found one instance of smi and this was a
a german lawyer and a kovic skeptic her materials are widely circulated in the monitor telegram
channels we saw but the most interesting aspect to it was that the administrators provided russian
and kazakh translations to her videos posts and articles um and this and in most cases her book
here translations of chapters were provided and they were getting into tens of thousands of views
and downloads so it is very interesting to see how it plays out in the
in terms of smes and how these agents work in promoting the narrative and again as they kind
of lend a certain legitimacy for the narrative that they're trying to promote so in this case
it's you know the coronavirus maybe is not necessarily uh teutonic it could be a bioweapon
we don't know how infectious it is and so forth and in this case bethlehem was one of these uh
sneeze that has been used extensively and um shared throughout the channels that be monitored
so the other tactic that we observed was content creation and the technique here the first one is
how we amplified those conspiracies by agents so when they narrativize when an operator narrativizes
an issue such as covet 19 and vaccinations conspiracy theories latch on to a narrative
you know there is the covet 19 theory of it you know that it's a bioweapon or so forth
but conspiracy theories that are may not necessarily be
related to it specifically will latch on to it and this is something that we're developing
it's sort of as a term as uh nested narrative so these sub-narratives that are amplified or
amplify the main narrative theme right so for instance that if it's covet is a bioweapon
then the bioweapon itself is developed for the united states military you know or the military
can't be trusted so you get into these whole different aspects of an ideology of theory so
from those that are um
anti-medicine to those that are anti-government so you see the narratives and the sub-narratives
or as you call nested narratives um reinforcing each other so the conspiratorial nested narratives
can be subsumed into the main narrative depending on a variety of factors but the
most successful ones are when operators uh accept them without little resistance so it's
uh in the case of like covid when it's introduced that covet is a bioweapon or so forth
well and so that's sort of another way to lens to this uh the youngsters who are
the most successful and are the most32o willing to support the saying so this is
a status quo Dave nylis just did a blog post on osgoode the great white people who have made
the nats of demonetization or ancestral
hol Zusammen
the ecosystem they're trying to build but in either case operators can achieve uh positive
gains by amplifying these conspiracy theories especially when uh with impactful use of the smees
and so what we see in both these cases in these cases is like on this left post right here
uh the western standard which is a libertarian-leaning canadian media organization
that has an extensive history of propagating pseudoscience and misdeed
info information um they interviewed a smee of some sort uh dr uh daniel nagase
a former doctor practicing in british columbia on uh pfizer and in particular they brought out
a recent pfizer report and authenticated uh pfizer report um that was released by the cdc
and they go uh step by step through uh what the pfizer report says and then starts uh
uh
breaking down where there's inconsistency or vagueness in terminology
and in doing so this creates a way of discrediting what pfizer is about if it's safe is it not safe
um should you actually get it and if there are alternatives and then in this case uh what uh
dr nagasi was uh saying is that he you should not take pfizer but instead use other remedies
such as your vermictin which he actually was promoting um and so in this case in this post
in particular it had around 222 000 views by members in a specific kazakhstan channel
but it should be noted that uh outside of our telegram channel we did note uh dr nagase he was
barred from practicing medicine uh prior to this interview because he was promoting ivermectin um
so but that was not covered at all during the actual interview itself
so in the next content aspect to it on the right post
uh this was a virtual roundtable discussion again this is um supported quote-unquote smees
where you had a german virologist and or non-virologist uh stefan lanca who asserts
that viruses don't exist um daniel browse who's a podcaster and then uh he's also his
moniker is podcaster o or podcast or zero and kate sukak uh who's the host of the program who's also
a russian but she is actually extensively used in social media both
on instagram twitter uh vikon kata and telegram for hosting content disinformation content
um with regards to uh copen 19 and vaccines specifically pfizer and similar to the previous
post uh this purported panel aimed to amplify why vaccines are government tools right um and
how they restrict things like natural freedom and how the covet 19 pandemic really isn't a pandemic
actually we're noticing a number of actual conspiracy theories latching onto the copin 19
theory that it's a fake pandemic that it was cooked up by the government uh and that it's
actually a political tool to restrict uh natural law or uh so and so forth
and so when we collected data at this time the video had been viewed around some 17 000 times
in the course of roughly one month so um and considering it was just in a few several
channels um that's quite a high amount of um views
and so in the other portion of uh content creation the other technique is uh providing or say
dropping evidence so evidence drops amplify narratives as well as serve as sort of in a
way a defensive role to buttress or strengthen support for those narratives so operators will
drop or fabricate evidence and both have been proven effective in other campaigns such as the
dnc email drops from 2016 by the gucifer 2.0 entity which we have found out to be you know
this was an overall russian influence operation uh but in doing so these were real artifacts
real evidence that were used to paint a certain narrative or to reinforce the narrative and this
is no this is not different from what we've witnessed in our in uh research in kazakhstan
so in the ecosystem in particular from what we found is that admins are prominent members of the
members in those channels would often drop evidence in one or two ways so a sensational
breaking news post so uh the red alert here's that's just coming out and oftentimes it would
be a fake news report or it would be uh from a credible source but then rewritten or stylized
in a way that made it see it sound differently so it'd be saying New York Times uh says kyber
uh Pfizer vaccine causes blood clots like J and J right when in fact it's saying Pfizer blood clots
I mean blood clots and J and J vaccine are a concern for those that have taken other vaccines
like Pfizer so they would manipulate what the breaking news might actually be um and then make
it so that it sounds more egregious or more damaging than what it is and then the other
portion is posts with links to multiple uh to various websites
so ranging from alternative medicine pseudoscience and general friends to all tech platforms
and as you can see in the example over here uh the posted links they are to allergic science
alleged scientific journals that garnered significant discussion across all the channels
and groups that we monitored and in particular there was one and again as you see from the first
uh image this is one of those uh data dumps or one of those uh drops of evidence where again
the
the admin actually posted some 50 different links to different articles and sites and so forth about
um issues that they that need to be addressed with regards to is the vaccine safe or should
we be concerned about covet and then this one this was through the supposed International
Journal of vaccine Theory practice and research which uh upon our research and looking it over
does not appear to appear to be a legitimate uh scientific Journal um
that is uh again of concern and this one again had a rate of roughly at least the mass link post had
around uh 12 000 views or nearly 13 000 views um and so wrapping up with what we have uh we wanted
to know again within Kazakhstan there's this also unique aspect to when you are
viewing information from an ecosystem and one of the things that we noticed was there is this narrative
variation so to speak on China's official vaccines um and throughout these um throughout the ecosystem
the channels we noticed that a lot of it was geared towards vaccine hesitancy vaccines are
unsafe and I would say on par obviously very negative but Chinese vaccines but namely Sinovacs
were rarely discussed or even mentioned even though it was the first approved foreign vaccine
in Kazakhstan that we know of alongside Kazakhstan's
vaccine kozvak and yet it's very interesting to see that the first foreign vaccine to be introduced
there is not at all mentioned if if anything so we calculated through the reference counts of all
the vaccines of prominence so around around just over 9 000 references uh Chinese developed
vaccines compromised just roughly three percent of total references so around
246 and that's Sinopharm and Sinovac collectively uh whereas Russia's Sputnik V generated the most
the second most uh where and then the US uh takes the the most at 69 percent and in particular what
we were looking at uh from a reference per month standpoint Sinovac's just referenced around got
around 22 references per month compared to Pfizer which had over 451 references and it's interesting
that an instance of like J&A with the blood cuts issue that only averaged out to about 84 references
per month but this was later in the year too when we were able to count these so when we look at the
strategic operation continued uh the the vaccine reference in total we can see that China's uh
vaccine Sinopharm and Sinovac barely registered even against the the the Sputnik V or even the
the lowest of the uh the US-based vaccines like Johnson and Johnson so it's very interesting to
see that this led us more credence to possibly seeing that this was Russian operators trying
to mitigate any negative impact from the Chinese given the amount of interest of Chinese investment
Chinese influence in Kazakhstan itself so we don't know definitively this is something that we would
love to go and further investigate
um but on the tail but on the whole is what we saw it it was very unique to see uh Chinese vaccines
not being um routinely um mentioned or even a negative or a positive light and so this is just
a tidbit of what we were trying to uh view within these telegrams within a lot of time for our
research so and with that uh I'd like to wrap up our um our lightning talk which has gone quite long
and I'm so thankful that we were able to do this uh I'd like to also thank my my colleague Dr Caroline
or bueno and how much uh I enjoyed working with at this so if you have any questions and comments
please direct it to either of us or both of us we'd be more than happy to talk and see more about
where we could possibly collaborate or if you had any questions in general we'd be more than
happy to answer them so thank you again and enjoy the rest of your conference