36C3 - Inside the Fake Like Factories

36C3 preroll music

Herald: OK. So inside the fake like
factories. I'm going to date myself. I

remember it was the Congress around
1990,1991 or so, where I was sitting

together with some people who came over to
the states to visit the CCC Congress. And

we were kind of riffing on how great the
internet is gonna make the world, you

know, how how it's gonna bring world peace
and truth will rule and everything like

that. Boy, were we naive, boy, where we
totally wrong. And today I'm going to be

schooled in how wrong I actually was
because we have Svea, Dennis and Philip to

tell us all about the fake like factories
around the world. And with that, could you

please help me in welcoming them onto the
stage? Svea, Dennis and Philip.

Philip: Thank you very much. Welcome to
our talk "Inside the Fake Like Factories

". My name is Philip. I'm an Internet
activist against disinformation and I'm

also a student of the University of
Bamberg.

Svea: Hi. Thank you that you listen to us
tonight. My name is Svea. I'm an

investigative journalist, freelance mostly
for the NDR and ARD. It's a public

broadcaster in Germany. And I focus on
tech issues. And I had the pleasure to

work with these two guys on, for me, a
journalistic project and for them on a

scientific project.
Dennis: Yeah. Hi, everyone. My name is

Dennis. I'm a PhD student from Ruhr
University Bochum. I'm working as a

research assistant for the chair for
System Security. My research focuses on

network security topics and Internet
measurements. And as Svea said, Philip and

myself, we are here for the scientific
part and Svea is for the journalistic part

here.
Philip: So here's our outline for today.

So first, I'm going to briefly talk about
our motivation for our descent into the

fake like factories and then we are going
to show you how we got our hands on ninety

thousand fake like campaigns of a major
crowd working platform. And we are also

going to show you why we think that there
are 10 billion registered Facebook users

today. So first, I'm going to talk about
the like button. The like button is the

ultimate indicator for popularity on
social media. It shows you how trustworthy

someone is. It shows how how popular
someone is. It shows, it is an indicator

for economic success of brands and it also
influences the Facebook algorithm. And as

we are going to show now, these kind of
likes can be easily forged and

manipulated. But the problem is that many
users will still prefer this bad info on

Facebook about the popularity of a product
to no info at all. And so this is a real

problem. And there is no real solution to
this. So first, we are going to talk about

the factories and the workers in the fake
like factories.

Svea: That there are fake likes and that
you can buy likes everywhere, it's well

known. So if you Google "buying fake
likes" or even "fake comments" for

Instagram or for Facebook, then you will
get like a hundreds of results and you can

buy them very cheap and very expensive. It
doesn't matter, you can buy them from

every country. But when you think of these
bought likes, then you may think of this.

So you may think of somebody sitting in
China, Pakistan or India, and you think of

computers and machines doing all this and
that they are, yeah, that they are fake

and also that they can easily be detected
and that maybe they are not a big problem.

But it's not always like this. It also can
be like this. So, I want you to meet

Maria, I met her in Berlin. And Harald, he
lives near Mönchen-Gladbach. So Maria, she

is a a retiree. She was a former police
officer. And as money is always short, she

is clicking Facebook likes for money. She
earns between 2 cent and 6 cent per like.

And Harald, he was a baker once, is now
getting social aid and he is also clicking

and liking and commenting the whole day.
We met them during our research project

and did some interviews about their likes.
And one platform they are clicking and

working for is PaidLikes. It's only one
platform out of a universe, out of a

cosmos. PaidLikes, they are sitting just a
couple of minutes from here in Magdeburg

and they are offering that you can earn
money with liking on different platforms.

And it looks like this when you log into
the platform with your Facebook account

then you get in the morning, in the
afternoon, in the evening, you get, we

call it campaigns. But these are pages,
Facebook fan pages or Instagram pages, or

posts, or comments. You can, you know, you
can work your way through them and click

them. And I blurred you see here the blue
bar; I blurred them because we don't want

to get sued from all these companies,
which you can see there. To take you a

little bit with me on the journey. Harald,
he was okay with us coming by for

television and he was okay that we did a
long interview with him, and I want to

show you a very small piece out of his
daily life sitting there doing the

household, the washing and the cleaning,
and clicking.

Come on. It could be like that. You click
and you earn some money. How did we meet

him and all the others? Of course, because
Philip and Dennis, they have a more

scientific approach. So it was also
important not only to talk to one or two,

but to talk to many. So we created a
Facebook fan page, which we call "Eine

Linie unterm Strich" (a line under a line)
because I thought, okay, nobody will like

this freely. And then we did a post. This
post, and we bought likes, and you won't

believe it, it worked so well; 222 people,
all the people I paid for liked this. And

then we wrote all of them and we talked to
many of them. Some of them only in

writing, some of them only we just called
or had a phone chat. But they gave us a

lot of information about their life as a
click worker, which I will sum up. So what

PaidLikes by itself says, they say that
they have 30000 registered users, and it's

really interesting because you might think
that they are all registered with 10 or 15

accounts, but most of them, they are not.
They are clicking with their real account,

which makes it really hard to detect them.
So they even scan their I.D. so that the

company knows that they are real. Then
they earn their money. And we met men,

women, stay-at-home moms, low-income
earners, retirees, people who are getting

social care. So, basically, anybody. There
was no kind of bias. And many of them are

clicking for two and more platforms. That
was, I didn't meet anybody who's only

clicking for one platform. They all have a
variety of platforms where they are

writing comments or clicking likes. And
you can make - this is what they told us -

between 15 euro and 450 euro monthly, if
you are a so-called power clicker and you

do this some kind of professional. But
this are only the workers, and maybe you

are more interested in who are the buyers?
Who benefits?

Dennis: Yeah. Let's come to step two. Who
benefits from the campaigns? So I think

you all remember this page. This is the
screen if you log into PaidLikes and,

you'll see the campaigns with, you have to
click in order to get a little bit of

money. And by luck we've noticed that if
you go over a URL, we see in the left

bottom side of the browser, a URL
redirecting to the campaign. You have to

click and you see that every campaign is
using a unique ID. It is just a simple

integer, and the good thing is, it is just
incremented. So now maybe some of you guys

notice what we can do with that. And yeah,
it is really easy with these constructed

URLs to implement a crawler for data
gathering, and our crawler simply

requested all campaign IDs between 0 and
90000. Maybe some of you ask why 90000? As

I already said, we were also registered as
click workers and we see, we saw that the

highest ID campaign used is about 88000.
So we thought OK, 90000 is a good value

and we check for every request between
these 90000 requests if it got resolved or

not, and if it got resolved, we redirected
the URL we present this source. That

should be liked or followed. And we did
not save the page sources from the

resolved URLs, we only save the resolved
URLs in the list of campaigns, and this

list was then the basis for further
analysis. And here you see our list.

Svea: Yes. This was the point when Dennis
and Philip, when they came to us and said,

hey, we have a list. So what can you find?
And of course we searched AfD, was one of

the first search queries. And yeah, of
course, AfD is also in that list. Maybe

not so surprisingly for some. And when you
look, it is AFD Gelsenkirchen. And the fan

page. And we asked AfD Gelsenkirchen, did
you buy likes? And they said, we don't

know how we got on that list. But however,
we do not rule out an anonymous donation.

But now you would think, Ok, they found
AfD; this is very expectable. But no, all

political parties – mostly local and
regional entities - showed up on that

list. So we have CDU/CSU. We have had FDP,
SPD, AfD, Die Grünen and Die Linke. But

not that you think Angela Merkel or some
very big Facebook fan pages just showed

up. No, no. Very small entities with a
couple of hundreds or maybe 10000 or 15000

followers. And I think this makes
perfectly sense, because somebody who has

already very, very much many fans
probably would not buy them there at

PaidLikes. And we asked many of them, and
mostly they could not explain it. They

would never do something like that. Yeah,
they were completely over asked. But you

have to think that we only saw the
campaign. The campaigns, their Facebook

fan pages, we could not see who bought the
likes. And as you can imagine, everybody

could have done it like the mother, the
brother, the fan, you know, the dog. So

this was a case we would have needed a lot
of luck to call anybody out of the blue

and then he would say, oh, yes, I did
this. And there was one, or there were

some politicians who admitted it. And one
of them, she did it also publicly and gave

us an interview. It's Tanja Kühne. She is
a regional politician from Walsrode,

Niedersachsen. And she was in the..., it
was the case that it was after an election

and she was not very happy with her fan
page. That is what she told us. She was

very unlucky and she wanted, you know, to
push herself and to boost it a little bit,

and get more friends and followers and
reach. And then she bought 500 followers.

And then we had a nice interview with her
about that. Show you a small piece.

Okay, so you see – answers are pretty
interesting. And she.. I think she was

that courageous to speak out to us. Many
of others did too, but only on the phone.

And they didn't want to go on the record.
But she's not the only one who answered

like this. Because, of course, if you call
through a list of potential fake like

buyers, of course they answer like, no,
it's not a scam. And I also think from a

jurisdictional way, it's it's also very
hard to show that this is fraud and a

scam. And it's more an ethical problem
that you can that you can see here, that

it's manipulative if you buy likes. We
also found a guy from FSP from the

Bundestag. But yeah, he ran away and
didn't want to get interviewed, so I

couldn't show you. So bought, or no
probably... He was like 40 times in our

list for various Facebook posts and videos
and also for his Instagram account. But we

could not get him on, we could not get him
on record. So what did others say? We, of

course, confronted Facebook, Instagram and
YouTube with this small research. And they

said, no, we don't want fake likes on our
platform. PaidLikes is active since 2012,

you know. So they waited seven years. But
after our report, at least, Facebook

temporarily blocked PaidLikes. And of
course, we asked them too, and spoke to

them and wrote with PaidLikes in
Magdeburg. And they said, of course, it's

not a scam because the click workers they
are freely clicking on pages. So, yeah,

kind of nobody cares. But PaidLikes, this
is only the tip of the iceberg.

Philip: So we also wanted to dive a little
bit into this fake like universe outside

of PaidLikes and to see what else is out
there. And so we did an analysis of

account creation on Facebook. So what
Facebook is saying about account creation

is that they are very effective against
fake accounts. So they say they remove

billions of accounts each year, and that
most of these accounts never reach any

real users and they remove them before
they get reported. So what Facebook

basically wants to tell you is that they
have it under control. However, there are

a number of reports that suggest
otherwise. For example, recently at NATO-

Stratcom Taskforce released a report where
they actually bought 54000 likes, 54000

social media interactions for just 300
Euros. So this is a very low price. And I

think you wouldn't expect such a low price
if it would be hard to get that many

interactions. They bought 3500 comments,
25000 likes, 20000 views and 5100

followers. Everything for just 300 Euros.
So, you know, the thing they have in

common, they are cheap, the fake likes and
the fake interactions. So we also have,

there was also another report from Vice
Germany recently. And they reported on

some interesting facts about automated
fake accounts. They reported on findings

that suggest that actually people use
internet or hacked internet of things

devices and to use them to create these
fake accounts and to manage them. And so

it's actually kind of interesting to think
about this this wa. To say, OK, maybe next

election your fridge is actually going to
support the other candidate on Facebook.

And so we also wanted to look into this
and we wanted to go a step further and to

look at who these people are. Who are
they, and what what are they doing on

Facebook? And so we actually examined the
profiles of purchased likes. For this we

created four comments under arbitrary
posts, and then we bought likes for these

comments, and then we examined the
resulting profiles of the fake likes. So

it was pretty cheap to buy these likes.
Comment likes are always a little bit more

expensive than other likes. And we found
all these offerings on Google and we paid

with PayPal. So we actually used a pretty
neat trick to estimate the age of these

fake accounts. So as you can see here, the
Facebook user ID is incremented. So

Facebook started in 2009 to use
incremented Facebook ID, and they use this

pattern of 1 0 0 0 and then the
incremented number. And as you can see, in

2009 this incremented number was very
close to zero. And then today it is close

to 40 billion. And in this time period,
you can see that you can kind of get a

rather fitting line through all these
points. And you can see that the likes are

in fact incremented, ... the account IDs
are in fact incremented over time. So we

can use this fact in reverse to estimate
the creation date of an account where we

know the Facebook ID. And that's exactly
what we did with these fake likes. So we

estimated the account creation dates. And
as you can see, we get kind of different

results from different services. For
example, PaidLikes, they had rather old

accounts. So this means they use very
authentic accounts. And we already know

that because we talked to them. So these
are very authentic accounts. Also like

Service A over here also uses very, very
authentic accounts. But on the other hand,

like service B uses very new accounts,
they were all created in the last three

years. So if you look at the accounts and
also from these numbers, we think that

these accounts were bots and on service C
it's kind of not clear, are these are

these accounts bots or are these
clickworkers? Maybe it's a mixture of

both, we don't know exactly for sure. But
this is an interesting metric to measure

the age of the accounts to determine if
some of them might be bots. And that's

exactly what we did on this page. So this
is actually a page for garden furniture

and we found it in our list that we got
from paid likes. So they bought, obviously

they were on this list for bought likes on
Facebook, on PaidLikes. And they caught

our eye because they had one million
likes. And that's rather unusual for a

shop for garden furniture in Germany. And
so we looked at this page further and we

noticed other interesting things. For
example, there are posts, all the time,

they got like thousands of likes. And
that's also kind of unusual for a garden

furniture shop. And so we looked into the
likes and as you can see, they all look

like they come from Southeast Asia and
they don't look very authentic. And we

were actually able to estimate the
creation dates of these accounts. And we

found that most of these accounts that
were used for liking these posts on this

page were actually created in the last
three years. So this is a page where

everything, from the number of people who
like to page to the number of people who

like to posts is complete fraud. So
nothing about this is real. And it's

obvious that this can happen on Facebook
and that this is a really, really big

problem. I mean, this is a, this is a shop
for garden furniture. Obviously, they

probably don't have such huge sums of
money. So it was probably very cheap to

buy this amount of fake accounts. And it
is really shocking to see how, how big,

how big the scale is of this kind of
operations. And so what we have to say is,

OK, when Facebook says they have it under
control, we have to doubt that. So now we

can look at the bigger picture. And what
we are going to do here is we are going to

use this same graph that we used before to
estimate the creation dates, but in a

different way. So we can actually see that
the lowest and the highest points of

Facebook IDs in this graph. So we know the
newest Facebook ID by creating a new

account. And we know the lowest ID because
it's zero. And then we know that there are

40 billion Facebook IDs. Now, in the next
step, we took a sample, a random sample

from these 40 billion Facebook IDs. And
inside of the sample, we checked if these

accounts exist, if this ID corresponds to
an existing account. And we do that because

we obviously cannot check 40 billion
accounts and 40 billion IDs, but we can

check a small sample of these accounts of
these IDs and estimate, then, the number

of existing accounts on Facebook and
total. So for this, we repeatedly access

the same sample of one million random IDs
over the course of one year. And we also

pulled a sample of 10 million random IDs
for closer analysis this July. And now

Dennis is going to tell you how we did it.
Dennis: Yeah. Well, pretty interesting,

pretty interesting results so far, right?
So we again implemented the crawler, the

second time for gathering public Facebook
information, the public Facebook account

data. And, yeah, this was not so easy as
in the first case. Um, yeah. As. It's not

surprising that Facebook is using a lot of
measures to try to block the automated

crawling of the Facebook page, for example
with IP blocking or CAPTCHA solving. But,

uh, we were pretty easy... Yeah, we could
pretty easy solve this problem by using

the Tor Anonymity Network. So every time
our IP got blocked by crawling the data,

we just made a new Tor connection and
change the IP. And this also with the

CAPTCHAs. And with this easy method, we
were able to to crawl all the Facebook,

and all the public Facebook data. And
let's have a look at two examples. The

first example is facebook.com/4. So the,
very, very small Facebook ID. Yeah, in

this case, we are, we are redirected and
check the response and find a valid

account page. And does anyone know which
account this is? Mark Zuckerberg? Yeah,

that's correct. This is this is a public
account for Mark Zuckerberg. Number four,

as we see, as we already saw, the other
IDs are really high. But he got the number

four. Second example was facebook.com/3.
In this case, we are not forwarded. And

this means that it is an invalid account.
And that was really easy to confirm with a

quick Google search. And it was a test
account from the beginning of Facebook. So

we did not get redirected. And it's just
the login page from Facebook. And with

these examples, we did, we did a lot of, a
lot more experiments. And at the end, we

were able to to build this tree. And, yeah,
this tree represents the high level

approach from our scraper. So in the,
What's that?

Svea: Okay. Sleeping.
Laughing

Dennis: Yeah. We have still time. Right.
So what? Okay, so everyone is waking up

again. Oh, yeah. The first step we call
the domain, www.facebook.com/FID. If we

get redirected in this case, then we check
if the, if the page is an account page. If

it's an account page, then it's an public
account like the example 4 and we were

able to save the raw data, the raw HTTP
source. If we, if it's not an account page

then everything is OK. If it's not, it's
not a public account and we are not able

to save any data. And if we call, if we
do, if we do not get redirected in the

first step, then we call the second
domain, facebook.com/profile.php?id=FID

with the mobile user agent. And if we get
redirected then, then again, it is a

nonpublic profile and we cannot save
anything. But, and if we get not

redirected, it is an invalid profile and
it is most often a deleted account. Yeah.

And yeah, that's the high level overview
of our scraper. And Phillip will now give

some more information on interesting
results.

Phillip: So the most interesting result of
this scraping of the sample of Facebook

IDs was that one in four Facebook IDs
corresponds to a valid account. And you

can do the math. There are 40 billion
Facebook IDs, so there must be 10 billion

registered users on Facebook. And this
means that there are more registered users

on Facebook than there are humans on
Earth. And also, it means that it's even

worse than that because not everybody on
Earth can have a Facebook account because

not everybody, you need a smartphone for
that. And many people don't have those. So

this is actually a pretty high number and
it's very unexpected. So in July 2019,

there were more than ten billion Facebook
accounts. Also, we did another research on

the timeframe between October 2018 and
today, or this month. And we found that in

this timeframe there were 2 billion new
registered Facebook accounts. So this is

like the timeframe of one year, more or
less. And in a similar timeframe, the

monthly active user base rose by only 187
million. Facebook deleted 150 million

older accounts between October 2018 and
July 2019. And we know that because we

pulled the same sample over a longer
period of time. And then we watched for

accounts that got deleted in the sample.
And that enables us to estimate this

number of 150 million accounts that got
deleted that are basically older than our

sample. So I made some nice graphs for
your viewing pleasure. So, again, the

older accounts were, just 150 million were
deleted since October 2018. These are

accounts that are older than last year.
And Facebook claims that since then, about

7 billion accounts got deleted from their
platform, which is vastly more than these

older accounts. And that that's why we
think that Facebook mostly deleted these

newer accounts. And if an account is older
than a certain age, then it is very

unlikely that it gets deleted. And also, I
think you can see the scales here. So, of

course, the registered users are not the
same thing as active users, but you can

still see that there are much more
registrations of, of new users than there

are active users. And there are new active
users during the last year. So what does

this all mean? Does it mean that Facebook
gets flooded by fake accounts? We don't

really know. We only know these numbers.
What Facebook is telling us is that they

only count and publish active users, as I
already said, that there is a disconnect

between this record, registered users and
active users and Facebook only reports on

the active users. Also, they say that
users register accounts, but they don't

verify them or they don't use them, and
that's how this number gets so high. But I

think that that's not really explaining
these high numbers and because that's just

by orders of magnitude larger than
anything that this could cause. Also, they

say that they regularly delete fake
accounts. But we have seen that these are

mostly accounts that get deleted directly
after their creation. And if they survive

long enough, then they are getting
through. So what does this all mean?

Svea: Okay, so you got the full load,
which I had like over two or three months.

And what for me was, was a one very big
conclusion was that we have some kind of

broken metric here, that all the likes and
all the hearts on Instagram and the

followers that they can so easily be
manipulated. And then it's it's so hard to

tell in some cases, it's so hard to tell
if they are real or not real. And this

opens the gate for manipulation and yes,
untrueness. And for economic losses, if

you think as somebody who is investing
money and or as an advertiser, for

example. And in the very end, it is a case
of eroding trust, which means that we

cannot trust these numbers anymore. These
numbers are, you know, they are so easily

manipulated. And why should we trust this?
And this has a severe consequence for all

the social networks. If you are still in
them. So what can be a solution? And

Philip, you thought about that.
Phillip: So basically we have two

problems. One is click workers and one is
fakes. Click workers are basically just

hyper active users and they are selling
their hyper activity. And so what social

networks could do is just make
interactions scarce, so just lower the

value of more interactions. If you are a
hyper active users, then your interaction

should count less than the interactions of
a less active user.

Mumbling
That's kind of solvable, I think. The real

problem is the authenticity. So if you if
you get stopped from posting or liking

hundreds of pages a day, then maybe you
just create multiple accounts and operate

them simultaneously. And this can only be
solved by authenticity. So this can only

be solved if you know that the person who
is operating the account is just one

person, is operating one account. And this
is really hard to do, because Facebook

doesn't know who is clicking. Is it a bot?
Is it a clickworrker, or is it one

clickworker for ten accounts? How does
this work? And so this is really hard for

the, for the social media companies to do.
And you could say, OK, let's send in the

passport or something like that to prove
authenticity. But that's actually not a

good idea because nobody wants to send
their passport to Facebook. And so this is

really a hard problem that has to be
solved. If we want to use social, social

media in a meaningful way. And so this is
what, what companies could do. And now...

Svea: But what do what you
could do. Okay. Of course, you can delete

your Facebook account or your Instagram
account and stop.

Slight Applause, Lauthing
Svea: Yeah! Stay away from social media.

But this maybe is not for all of us a
solution. So I think be aware, of course.

Spread the word, tell others. And if, if
you, if you like, then and you get more

intelligence about that, we are really
happy to dig deeper in these networks. And

and we will go on investigating and so at
last but not least, it's to say thank you

to you guys. Thank you very much for
listening.

Applause
Svea: And we did not do this alone. We are

not three people. There are many more
standing behind and doing this, this

beautiful research. And we are opening now
for questions, please.

Herald: Yes. Please, thank Svea, Phil and
Dennis again.

Applause
And we have microphones out

here in the room, about nine of them,
actually. If you line up behind them to

ask a question, remember that a question
is a sentence with a question mark behind

it. And I think I see somebody at number
three. So let's start with that.

Question: Hi. I, I just have a little
question. Wouldn't a dislike button, the

concept of a dislike button, wouldn't that
be a solution to all the problems?

Phillip: So we thought about recommending
that Facebook ditches the like button

altogether. I think that would be a better
solution than a dislike button, because a

dislike button could also be manipulated
and it would be even worse because you

could actually manipulate the network into
down ranking posts or kind of not showing

posts to somebody. And that, I think would
be even worse. I imagine what dictators

would do with that. And so I think the
best option would be to actually not show

off like, like counts anymore and to this,
to actually make people not invest into

these counts if they become meaningless.
Herald: I think I see a microphone 7, up

there.
Question: Hello. So one question I had is

you are signed creation dates to IDs. How
did you do this?

Phillip: So, we actually knew the creation
date of some accounts. And then we kind of

interpolated between the creation dates
and the IDs. So you see this black line

there. That's actually our, our
interpolation. And with this black line,

we can then estimate the creation dates
for IDs that we do not yet know because

they did, kind of fill in the gaps.
Q: Follow up question, do you know why

there are some points outside of this
graph?

Phillip: No.
Q: No? Thank you.

Herald: So there was a question from the
Internet.

Question: Did you report your findings to
Facebook? And did they do anything?

Svea: Because this research is very new,
we, we just recently approached them and

showed them the research and we got an
answer. But I think we also already showed

the answer. It was that they, I think that
they only count and publish active users.

They could, they did not want to tell us
how many registered users they have, that

they say, oh, sometimes users register
accounts, but don't use them or verify

them. And that they regularly delete fake
accounts. But we hope that we get into a

closer discussion with them soon about
this.

Herald: Microphone two.
Question: When hunting down the bias of

the campaigns, did you dig out your own
campaign line, Line below the line? No,

because they stopped scraping in August.
And I, you stopped scraping in August. And

then I started, you know, the whole
project started with them coming to us

with the list. And then we thought, oh,
this is very interesting. And then the

whole journalistic research started. And,
but I think if we, I think if we would do

it again, of course, I think we would find
us. We all also found there was another

magazine, and they did, also a test, paid
test a couple of years ago. And we found

their campaign.
Phillip: So, so we we actually did another

test. And for the other test, I noted we
also got like this ID, I think. And it

worked to plug it into the URL and then we
also got to redirected to our own page. So

that worked.
Q: Thank you.

Herald: Microphone three.
Question: Hi. I'm Farhan, I'm a Pakistani

journalist. And first of all, I would like
to say that you were right when you said

that there might be people sitting in
Pakistan clicking on the likes. That does

happen. But my question would be that
Facebook does have its own ad program that

it aggressively pushes. And in that ad
program, there is also options whereby

people can buy likes and comments and
impressions and reactions. Did you, would

you also consider those as a fake? I mean,
that they're not fake, per se, but they're

still bought likes. So what's your view on
those? Thank you.

Phillip: So, when you buy ads on Facebook,
then, so, what you what you actually want

to have is fans for your page that are
actually interested in your page. So

that's kind of the difference, I think to
the, to the paid likes system where the

people themselves, they get paid for
liking stuff that they wouldn't normally

like. So I think that's the fundamental
difference between the two programs. And

that's why I think that one is unethical.
And one is not really that unethical.

Svea: The very problem is if you, if you
buy these click workers, then you have

many people in your fan page. They are not
interested in you. They don't care about

you. They don't look at your products.
They don't look at your political party.

And then often the people, they
additionally, they make Facebook ads, and

these ads, they are shown, again, the
click workers and they don't look at them.

So, you know, people, they are burning
money and money and money with this whole

corrupt system.
Herald: So, microphone two.

Question: Hi. Thanks. Thanks for the talk
and thanks for the effort of going through

all of this project. From my
understanding, this whole finding

basically undermines the trust in
Facebook's likes in general, per se. So I

would expect now the price of likes to
drop and the pay for click workers to drop

as well. Do you have any metrics on that?
Svea: The research just went public. I

think one week ago. So, so what we have
seen as an effect is that Facebook, they

excluded paid likes for, for a moment. So,
yes, of course, one platform is down. But

I think there are so many outside. There
are so many. So I think...

Q: I meant the phenomenon of paid likes,
not the company itself. Like the value of

a like as a measure of credibility...
Phillip: We didn't...

Q: ...is declining now. That's my, that's
my...

Svea: Yes. That's why many people are
buying Instagram hearts now. So, so, yes,

that's true. The like is not the fancy hot
shit anymore. Yes. And we also saw in the

data that the likes for the fan pages,
they rapidly went down and the likes for

the posts and the comments, they went up.
So I think, yes, there is a shift. And

what we also saw in that data was that the
Facebook likes, they, they went down from

2016. They are rapidly down. And what is
growing and rising is YouTube and

Instagram. Now, everything is about,
today, everything is about Instagram.

Q: Thanks.
Herald: So let's go to number one.

Question: Hello and thank you very much
for this fascinating talk, because I've

been following this whole topic for a
while. And I was wondering if you were

looking also into the demographics, in
terms of age groups and social class, not

of the people who were doing the actual
liking, but actually, you know, buying

these likes. Because I think that what is
changing is an entire social discourse on

social capital and, the bold U.S. kind of
term, because it can now be quantified. As

a teacher, I hear of kids who buy likes to
be more popular than their other

schoolmates. So I'm wondering if you're
looking into that, because I think that's

fascinating, fascinating area to actually
come up with numbers about it.

Svea: It definitely is. And we were all so
fascinated by this data set of 90,000 data

points. And what we did was, and this was
very hard, and was that we tried it, first

of all, to look who is buying likes, like
automotives, you know, to to, this some,

you know, what, what kind of branches? Who
is in that? And so this was this was

doable. But to get more into demographics,
you would have liked to, to crawl, to

click every page. And so we we did not do
this. What we did was, of course, that we

that we were a team of three to ten people
and manually looking into it. And what we,

of course, saw that on Instagram and on
YouTube, you have many of these very young

people. Some of them, I actually called
them and they were like, Yes, I bought

likes. Very bad idea. So I think yes, I
think there is a demographic shift away

from the companies and the automotive and
industries buying Facebook fan page likes

to Instagram and YouTube wannabe-
influencers.

Q: Influencers, influencer culture is
obviously...

Svea: Yes. And I have to admit here we, we
showed you the political side, but we have

to admit that the political likes, they
were like this small in the numbers. And

the very, very vast majority of this data
set, it's about wedding planners,

photography, tattoo studios and
influencers, influencers, influencers and

YouTubers, of course.
Q: Yes. Thank you so much.

Herald: So we have a lot of questions in
the room. I'm going to get to you as soon

as we can. I'd like to go to the Internet
first.

Signal Angel: Do you think this will get
bit better or worse if people move to more

decentralized platforms?
Phillip: To more what?

Svea: If it get better or worse.
Dennis: Can you repeat that, please?

Herald: Would this issue get better or
worse if people move to a more

decentralized platform?
Phillip: Decentralized. decentralized,

okay. So, I mean, we can look at, at the,
this slide, I think, and think about

whether decentralized platforms would
change any of these, any of these two

points here. And I fear, I don't think so,
because they cannot solve the interactions

problem that people can be hyperactive.
Actually, that's kind of a normal thing

with social media. A small portion of
social media users is much more active

than everybody else. That's kind of. You
have that without paying for it. So

without even having paid likes, you will
have to consider if social media is really

kind of representative of the society.
But, and the other thing is authenticity.

And also in a decentralized platform, you
could have multiple accounts run by the

same person.
Herald: So, microphone seven, all the way

back there.
Question: Hi. Do you know if Facebook even

removes the likes when they delete fake
accounts?

Svea: Do you know that?
Phillip: No, we don't know that. No, we

don't. We don't know. We know they delete
fake accounts, but we don't know if they

also delete the likes. I know from our
research that the people we approached,

they did not delete the click workers.
They get...

Herald: Microphone two.
Question: Yeah. Hi. So I have a question

with respect to this, one out of four
Facebook accounts are active in your, in

your test. Did you see any difference with
respect to age of the accounts? So is it

always one out the four to the entire
sample? Or does it maybe change over the,

over the like going from a zero ID to,
well, 10 billion or 40 billion?

Phillip: So you're talking about the
density of accounts in our ID?

Q: Kind of.
Phillip: So, so there are changes over

time. Yeah. So I guess I think now it's
less than it was before. So now they are

less than for then, and before it was more
and so I think it was. Yeah. I don't know.

Q: But you don't see anything specific
that now, only in the new accounts, only

one out of 10 is active or valid and
before it was one out of two or something

like that.
Phillip: It's not that extreme. So it's

less than that. It's kind of...
Dennis: We have to say we did not check

this, but there were no special cases.
Phillip: But it changed over time? So

before it was less and, before it was more
and now it is less. And so what we checked

was whether an ID actually corresponds to
an account. And so this metric, yeah. And

it changed a little bit over time, but not
much.

Herald: So, so number three, please.
Question: Yeah. Thank you for a very

interesting talk. At the end, you gave
some recommendations, how to fix the

metrics, right? And it's always nice to
have some metrics because then, well, we

are the people who deal with the numbers.
So we want the metrics. But I want to

raise the issue whether quantitative
measure is actually the right thing to do.

So would you buy your furniture from store
A with 300 likes against store B with 200

likes? Or would it not be better to have a
more qualitative thing? And to what extent

is a quantitative measure maybe also the
source of a lot of bad developments we see

in social media to begin with, even not
with bot firms and anything, but just

people who go for the quick like and say
Hooray for Trump and then get, whatever,

all the Trumpists is liking that and the
others say Fuck Trump and you get all the

non Trumpists like that and you get all
the polarization, right? So, Instagram, I

think they just don't just display their
like equivalent anymore in order to

prevent that, so could you maybe comment
on that?

Svea: I think this is a good idea, to, to
hide the likes. Yes. But I you know, we

talked to many clickworkers and they do a
lot of stuff. And what they also do is

taking comments and doing copy paste for
comments section or for Amazon reviews.

So, you know, I think it's really hard to
get them out of the system because maybe

if the likes are not shown and if and when
the comments are counting, then you will

have people who are copy pasting comments
in the comments section. So I really think

that the networks, that they really have
an issue here.

Herald: So let's try to squeeze the last
three questions now. First, number seven,

really quick.
Question: Very quick. Thank you for the

nice insights. And I have a question about
the location of the users. So you made

your point that you can analyze by the
metadata where, uh, when the account was

made. But how about the location of the
followers? Is there any way to analyze

that as well?
Phillip: So we can only analyze that if

the users agreed to share it publicly and
not all of them do that, I think often a

name check is often a very good way to
check where somebody is from. For these

fake likes, for example. But as I said, it
always depends on what the user himself is

willing to share.
Herald: Internet?

Signal Angel: Isn't this just the western
version of the Chinese social credit

system? Where do we go from here? What is
the future of all this?

Svea: Yeah, it's dystopian, right? Oh,
yeah, I don't, after this research, you

know, for me, I deleted my Facebook
account like one or two years ago. So this

does you know, this did not matter to me
so much. But I stayed on Instagram and

when I saw all this bought likes and
abonnents and followers and also YouTube,

all this views, this, because the click
workers, they also watch YouTube videos.

They have to stay on them like 40 seconds,
it's really funny because they hate

hearing like techno music, rap music, all
40 seconds and then they go on. But when I

sit next to Herald for two hour, three
hours, I was so desillusionated about all

the social network things. And and I
thought, OK, don't count on anything. Just

if you like the content, follow them and
look at them. But don't believe anything.

That was my personal take away from this
research.

Herald: So very last question, microphone
two.

Question: A couple of days ago, The
Independent reported that Facebook, the

Facebook App was activating the camera
when reading a news feed. Could this be in

use in the context of detecting fake
accounts?

Svea: I don't know.
Phillip: So, I think that that in this

particular instance that it was probably a
bug. So, I don't know, but I mean that the

people who work at Facebook are, not all
of them are like crooks or anything that

they will deliberately program this kind
of stuff. So they said that it was kind of

a bug from from an update that they did.
And the question is whether we can

actually detect fake accounts with the
camera. And the problem is that current, I

don't think that current face recognition
technology is enough to detect that you

are a unique person. So there are so many
people on the planet that probably another

person who has the same face. And I think
the new iPhone, they also have this much

more sophisticated version of this
technology. And even they say, OK, there's

a chance of one in, I don't know, that
there is somebody who can unlock your

phone. So I think it's really hard to do
that with, do that with recording

technology, to actually prove that
somebody is just one person.

Herald: So with that, would you please
help me thank Svea, Dennis and Philip

one more time for this fantastic
presentation! Very interesting and very,

very disturbing. Thank you very much.
Applause

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