Information Epidemics and Collective Action
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00:00
Group actionHypermediaMultiplication signProcess (computing)Software frameworkOrder (biology)TrailCognitionControl flowShared memoryContext awarenessField (computer science)InternetworkingSoftwarePresentation of a groupSelf-organizationFrame problemMessage passingLecture/Conference
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Message passingSoftware frameworkInteractive televisionMultiplication signSoftwareOpen setGroup actionLecture/Conference
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MathematicsSoftwareMathematical analysisGraph (mathematics)Endliche ModelltheorieConnected spaceOrder (biology)InformationInteractive television
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1 (number)Computer networkDynamical systemInformationEndliche ModelltheorieRevision controlObservational studyLevel (video gaming)Multiplication signSoftwareLecture/Conference
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InformationInteractive televisionGroup actionDynamical systemEndliche ModelltheorieMultiplication signProcess (computing)Graph (mathematics)Level (video gaming)Physical systemData conversionTwitterSoftwareThresholding (image processing)Mathematical analysisVideoconferencingArtificial neural networkFamilyPressureCognitionPoint (geometry)Differential equationCASE <Informatik>Lecture/Conference
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Different (Kate Ryan album)SoftwareType theoryInformationArtificial neural networkData structureNumberConnected spaceWebsiteTwitterFacebookRandom graphInternetworkingDegree (graph theory)Lecture/ConferenceComputer animation
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SoftwareGroup actionNumberConnected spaceFamilyRandom graphUniverse (mathematics)Data structureStandard deviationComputer animation
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SoftwareNormal (geometry)Goodness of fitData structureDifferent (Kate Ryan album)Random graphFamilyGroup action
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outputCASE <Informatik>Impulse responseSoftwareFreewareScaling (geometry)Multiplication signInformationGroup actionComputer networkRandomizationKeyboard shortcutRandom graphChannel capacityData structureOscillationExistencePoint (geometry)Order (biology)Extreme programmingComponent-based software engineeringGoodness of fitTwitterMessage passingDifferent (Kate Ryan album)Form (programming)Distance
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InformationGroup actionChannel capacitySoftwareConnected spaceCore dumpShared memoryMultiplication signMessage passingRoboticsRight angleOrder (biology)Observational studyDifferent (Kate Ryan album)Strategy gameMathematical singularityWeb pageMultiplicationCASE <Informatik>Broadcasting (networking)Basis <Mathematik>Extreme programmingService-oriented architectureComputer virusTelecommunicationComponent-based software engineeringFacebookoutputGodOperator (mathematics)Lecture/Conference
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Right angleConnected spaceMessage passingGroup actionObservational studyInformationstheorieLevel (video gaming)InformationComputer animation
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FacebookSoftwareData structureGroup actionMathematicsDifferent (Kate Ryan album)Source code
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SoftwareMathematicsGroup actionMereologyState observerFrequencyMultiplication signDistanceLecture/Conference
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Data structureView (database)Field (computer science)MathematicsAbstractionPresentation of a groupGroup actionOrder (biology)InformationStrategy gameFacebookPoint (geometry)Message passingService-oriented architectureMultiplication sign1 (number)INTEGRALProcess (computing)BlogNumberSoftwareSystem callComputer virusReplication (computing)Computer animation
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Interactive televisionField (computer science)InformationMereologyTelecommunicationGroup actionScaling (geometry)Different (Kate Ryan album)CircleEmailView (database)Lecture/ConferenceMeeting/Interview
Transcript: English(auto-generated)
00:16
Hello, my name is Dimitri and as he already said I work in notice labs, which is a research
00:23
organization that studies how the framework Framework of networks can be used to understand cognition and social processes First of all, I'll just say what I'm going to do. I'll just make Like a half an hour long presentation of some of the main ideas
00:43
In the network analysis that can be used to understand protest movements and Because there is not so much time if you have any questions. We either can have them after the session or outside During the breaks and so on so I'm very open to speak about it after and the second thing is that I just want to
01:03
Address the context where this talk is actually happening. It's the revolt track and most of the discussions In this track are focusing on Protest movements and
01:20
Somehow We all share a similar understanding of what the protest movement is. It's when a group of people shares a certain idea becomes fascinated with it strongly enough that they unify for a collective action in order to Spread this idea to the rest of the people who might not always be
01:44
Sharing the same values and we've seen it happening during the last years in the Occupy Wall Street movement in the protests in Africa in Russia and so on and Sometimes it worked well, and sometimes it didn't We also know that social media plays an important role in this process. We also know that the government's they started to
02:07
Also do some kind of crackdown on the freedom of the internet in order to stop these movements and sometimes even use the same Techniques in order to counteract protest movements, so we kind of know what's what's happening in the field generally But what I want to speak about today
02:22
And it's something that I feel is often missing from this discourse are the technicalities of how protest movements actually Work and function. How does it happen that people? Get into a certain idea at the same time, how do they unify for a collective action?
02:42
How can we ensure that a message spreads through network in the most efficient way to a large group of people? How can we structure our interactions in the ways that would? Enable the network be robust against external influence and at the same time
03:00
Open and adaptable enough so that it could be responsive to whatever challenges it encounters in the outside world and All these questions are very complex because we're dealing with a lot of individuals That interact and the framework of network analysis can be very useful to think about this phenomena. So
03:22
In network analysis the People Are represented as nodes and their interactions are the connections between them once we start seeing communities as networks we can use various tools from Graph analysis and mathematics in order to see how
03:42
these communities come together proliferate information and fall apart and One of the basic models that's used when we talk about information contagion and Dissemination of information and networks are the epidemic models, which are usually used to study diseases
04:02
I'll just go through them quickly because we didn't have so much time One of the basic ones is si are so that means that the node can be in several different stages It can be susceptible as I infected and are recovered or a more Complex version of the same model is susceptible infected recovered susceptible again back to infected so
04:28
these very basic epidemic models can then be applied to any dynamics That involves people getting into a certain idea. So for example, they can be susceptible to something
04:43
Let's say like buying new Nike sneakers or something like this then become infected with the idea So they buy them then the fashion wears off They recover then the new fashion comes again. They go back to being infected with a certain idea so this is a basic epidemic model how it works and
05:04
Then one other important concept here are information cascades It's heard like behavior influenced by the others when the conversion threshold is exceeded So let's say that the node is you and this is all the friends or family that you have a
05:21
certain time passes by and A small proportion of your surrounding becomes interested in a certain idea Let's say they think that the government system in Germany sucks and they want to change it So they will tell you that okay something has to be done But because it's only let's say 10% of the people that surround you it's not enough for you to change the opinion so some time passes even more and
05:45
You have already 70% of your surrounding Interested in the same idea or maybe believing in a certain thing or adopting a certain trend So you become much more susceptible to? Accepting it also because of the social pressure because you hear it all the time and so on
06:01
So at some point you also become infected with a certain idea that is surrounding you So this is a basic model of how informational cascades work So on the global level this is how the contagion occurs, I don't know if I can play this video here no
06:20
We have different groups inside the networks that are susceptible to a Certain piece of information they become infected then they spread information further to other groups Some of the groups recover during the process and this kind of dynamics happens globally When we model interaction processes in this way, then we can use the tools from
06:45
graph analysis Also differential equations to see how exactly does it happen that information spreads through networks? What network structures are the most conducive to? spread information What network structures are better to make sure that information spreads simultaneously?
07:06
in a synchronized way and so on So I'll just go quickly through the different types of networks that Exist so one of the most common one is scale-free network it's when most of the nodes inside the network have very few connections and a few but significant number of nodes of
07:28
Very well connected so the number of connections among the nodes is distributed unequally they have a Network
07:42
Internet is structured for example like this you have websites like Twitter and Google and Facebook where most of the people go and Most of the websites on the internet are maybe only visited by the people who actually created them So this is scale-free network structure. Then we have another type of network random network It's where most of the nodes have more or less the same number of connections
08:04
And there is a few deviations Very few nodes are very well connected and very few nodes have very few connections But most of the nodes they share more or less the same number of connections This is a situation that you normally encounter at your workplace or in the university where everyone knows each other
08:21
So everyone has more or less the same number of connections in the group And then we have also small world networks, which are very typical for whatever social structures We're involved in Our friends family and so on So this means that we still have a very well connected network almost as well connected as the random network
08:42
But the community structure inside the network is quite prominent So we have different groups of nodes Which are more densely connected together than with the rest of the network So we have all these different communities that interact together globally as well. This is a very typical structure for Normal social networks that we have your friends, maybe your family. It's all the different groups that have
09:06
weak ties together and Form different communities so when we talk about dissemination of information in networks the structure of the network is very important because a
09:20
few different independent researchers both in Epidemics and in viral marketing they found out that for example if we talk about random network where most of the people know each other and a certain disease or Information enters this network. It's much more susceptible to high amplitude
09:41
oscillations, so the lifetime of infection is Short-lived but at the same time such random networks are much more likely to synchronize globally so basically if you Have a group of people where everyone knows each other and everyone interacts all the time and you communicate a certain message
10:00
to a large enough proportion that informational cascades occur then You will ensure that There is certain trends happening in the network that a lot of people become interested in the same idea at the same time However, it will be quite short-lived So it will be a short-lived trend that disappears after a while on the other extreme
10:22
We have also networks that are more like scale free with the prominent community structure Such networks are very good in proliferating information for longer distances So you ensure that almost everyone in the network receives the message, but it they're much less likely to synchronize So the global cascades are much less likely to occur and then we have something in the middle
10:43
Which is mostly the case of scale free networks where there's different prominent communities that are also Connected together through random shortcuts such networks can synchronize easily and at the same time They can also proliferate information globally very
11:02
Efficiently So when we talk about disseminating information and networks the introduction of random shortcuts in the community structure, that's quite distinct is very important and This enables the network to maintain The capacity to synchronize globally, but at the same time to also have enough resistance
11:25
against this kind of oscillatory movement where it can change opinion very quickly or where a Certain piece of information or a trend can wear off So introducing random shortcuts in the community structure is very important for actually disseminating information in networks
11:40
Then we have also another important point. It's the existence of the giant component So most of the nodes in the network should belong to the same interconnected structure a very good example is for example Right now here. I don't know how many people know each other, but after we finish this talk if you all
12:02
Knew each other and you were interacting with each other It would be much easier to continue this discussion in this group However, because everyone is more or less disconnected It makes it very difficult for this network that we also temporarily formed here To actually generate some information on its own. It always needs external
12:22
Input and impulse in order to kind of get involved into certain things So when you communicate information to large groups of people It's important to make sure first that they are Interconnected so that they have the actual capacity to interact together and then it will make it much easier for
12:41
you to communicate a Certain message to this group of people and what happens on Facebook quite often with pages that are established for brands or for protest movements is that Lots of people that belong to the page or that belong to the group are actually not connected to each other So they don't have their friends belonging to the same group
13:00
That means that you communicate a certain message to them, but they don't spread it on their own So they always need external input in order to continue Acting Within the constellation So forming giant component and connections between the nodes is very important for information to spread through Then also one other important thing is when we communicate
13:22
To a large group of people. It's important to start with the group of Interconnected nodes and then this group will spread the information to the rest of the network through the connections that it has to other groups At the same time This also tells us what the possible strategy of resistance could be if we have a network that we don't want to be
13:43
Influenced too easily. So in this case Studies in epidemiology they found that the least efficient immunization strategy was to Immunize a certain proportion of groups in the population So for example the households and the most efficient immunization strategy was to immunize a certain proportion
14:04
within each group, so That means that if we want to be able to resist Being influenced easily the network that we're operating It should be comprised of groups that don't share the same opinion So there is maybe some confrontation even within the groups
14:20
That means they cannot easily synchronize together and that means they wouldn't also spread information globally So these are the two extremes that we can have on one side groups That share a certain consensus and that makes it easy to communicate certain piece of information to them that they spread it further in the network And on another side as a strategy of resistance to have groups that slightly disagree
14:42
So it makes it harder for them to synchronize globally So basically what I want to emphasize here is that if we are talking about a group of people Which is able to Unify for a collective action and share the same idea of a certain thing
15:03
It's important that every member of this group acts on the basis of polysingularity where they belong Simultaneously to different communities that are distinct from each other that don't relate together But that enables them to have a multiplicity of different opinions and to choose at each time
15:21
Which group they belong to and at the same time be open to any other information from other groups Another important idea when we spread information is to focus on brokers on the people that connect different groups together Because then they will disseminate information through the rest of the network and
15:40
Of course the message itself. It should be structured like a virus So it should have the capacity to replicate itself and there was a very interesting study done of London riots by the garden Where they found that the rumors that started with the question were much longer Lived then the rumors that started with a certain assertion. So for example, if you want to spread a rumor, it's much easier if you say
16:04
Not just like Angela Merkel disappeared, but you write is it true that build wrote that Angela Merkel disappeared? so you start with the question and there's a lot of layers of truths that have to be actually unfolded in order to get to the core of the message and to Confirm it or not. So starting with the question is always good to make sure that information goes viral
16:25
it's also important to recontextualize so to know the kind of Mental map of the group that you address so you can propose something that relates to the information They already have but that still also carries some kind of novelty in this message
16:40
and of course, it's important that the purpose of The group is related to the message that you communicate So it should reiterate the purpose that brings people together if you try to communicate to the group that's against Putin that Animal rights are important. It's not going to work so well, but if you say that They should believe in the fact that animal rights are important because it will help to put Putin down
17:04
Maybe it will work better. So there should be always connection to the purpose that holds the group together and One other important study found that once 10% of people is committed enough to certain idea They can spread it easily through the rest of the network Then I'll just go quickly
17:20
In a couple of minutes and then I will be done through the Russian protest movement We analyzed different Facebook groups that were established to actually Be able to do this protest that happened in December and January in Moscow and one of the groups was Putin must leave we found that We analyzed it actually once in December and once in January
17:43
2012 after a big demonstration that happened in Moscow and we found that while the group was able to attract new members the Community structure inside the group didn't change and also the communities were not very well connected together More than half of the nodes didn't have any friends that belong to the same network
18:03
So it made it very hard for this network to actually introduce any change because it was not connected enough and it was not open enough to external Challenges that it faced and also when we analyzed which people actually belong to each group We found that it was a highly politicized group that consistent of people who worked with
18:24
opposition leaders There's a group here where it's Georgian activists who are against Putin because of that war that happened before So it was a highly politicized group with a lot of ideology inside on the other hand another group that worked in a much More efficient way and that was much more successful and implementing change was the volunteer and activist group
18:45
That was just gathering people to be observers at the next presidential elections over the same period of time This group managed to attract 50% more members. So it rose almost twice and then The members that were already part of the network. They actually connected together much more
19:02
It had much less nodes that didn't have any other friends in the network So only one third of the people didn't know anyone else But two-thirds were actually connected to each other in the network and This group was much more interconnected. It had lower average path the distance
19:22
You have to travel in between the nodes and the community is actually what was most interesting. They changed the structure so the hubs which were important they lost their importance and they gave way to the Newcomers from the periphery who were able to actually also influence the kind of processes that happen within the group and
19:42
When we analyzed who is are the member of this network? We found that it was mainly journalists and bloggers who were not politically active before So this group that was formed for a very practical purpose was much more efficient in Evolving in something that could be useful and that actually worked much better
20:01
And now that we look in retrospective the political change didn't really happen But what happened is that people they for the first time in Russia got a taste for actually actively participating in very practical and important processes of election of observing election and of being active in this field
20:21
So successful groups are the ones where people talk to each other where the periphery is Integrated where hubs are leaving the center to form new groups when small number of orphans are people who are not connected exist And when the unifying slogan is not something Political and general and abstract but more a call to action then people are constantly reminded about the purpose that brings them together
20:46
So just to go through quickly the main points that I made in this presentation It's important for information dissemination that there is a prominent community structure that has random shortcuts in between the communities It's important to focus on densely connected homogeneous group in order to spread information
21:04
Information brokers are important because they connect different communities together so they can be addressed in order to proliferate information inside the network and message should be structured as a virus in order to be able to replicate itself, of course I looked into all these details from the point of view of
21:21
How to make it easy for information to spread through but we can use exactly the same strategies to also be able to resist any external influence that might be Encountered through social networks and for example the way how Facebook makes people interact where it locks people into Informational bubbles where we are surrounded by quite homogeneous community actually makes it much easier for
21:45
External agents to influence people and influence the behavior. So it's always important to resist I think this kind of drive that exists in society right now to filter out your circle of communication to one group, but to always
22:00
still be able to go into different groups and be part of different communities maybe even have different lives and That would enable you to have an overview of what's happening on a global scale while also being able to Be active in a certain field as long as you feel it's important So these are my contact details if you want to speak about it after you're very welcome to send me an email
22:23
But we can also speak after or if you have some questions right now I think I have maybe a few minutes your view very welcome to ask them Thank you
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