 And I would like to a little bit reverse this approach and ask Mexico a question to Victoras when you're down there in the cyberspace and you're not thinking whether this piece of information is credible or not, or the source is credible or not. But you're on the other side and you want to look out for malign actors and look for the bad guys, essentially saying. What is the difference in your thinking and what do you actually do to get them? Yeah, hello everyone. Sure, it's a very good question. So for that, I will show some slides to give a better understanding of what we do and what approach we take for that. Just shortly, so now currently we're working in six countries, Lithuania, Latvia, Estonia, Poland and North Macedonia and United States. And every month we analyze, we receive about one million content pieces and we analyze manually eight to 10,000 content pieces each month. We produce quite a lot of reports from that that I will share some processes, how things work. So this is the main process, how information is analyzed. Currently we analyzing in 26 languages about one million content pieces per month. So we use AI, power technology to do some process of automation. So AI cannot do everything, it's more as a feature of automation of some process. It's not a general AI, but it can help us to create scoring mechanisms, do the topic recognition and putting information in different shelves. So it would be easier for analysis. This information comes in all kinds of shapes, but we quite know well what are the main narratives, long-term narratives, also the topic narratives that change over time, but we quite know them well and it helps us a lot easier to find this information. Also we use citizens in Baltics, they are called Lithuanian elves or just elves. So they are active citizens that support us and help to analyze information that is received and also they cooperate with analysts. Then we have this labeling process where the analysis is done, each content piece is reviewed manually and then the reports are prepared, articles are prepared and they being published to stakeholders and also to general media to inform citizens of what's actually happening there. When we speak about different domains and so now we use just two types of information, either it's disinformation or misinformation. Typically the main difference is the intent or how often that author or domain or organizations tend to spread this information. What I could suggest for every citizen person is to acquire and use more of a critical thinking to understand what's happening there. And it's actually quite easy, it's not something that is very complicated. So you need to always ask yourself first thing, who is the source? Who is the author? Just click on him or her, check what he's writing about, what other issues is the author in the article? There are other particles that have no author and that already suggests that there might be some credibility questions. Is the source known? Whom that source belongs, how it's financed? So some of these questions can be very easily Googled. If you just spot something in social media, a very popular link, just Google it and maybe you'll find the Wikipedia page, maybe you'll find some about page or other information. So anytime you feel something is quite emotional or impactful, the first step would be just think and the second step is just to do a little bit of Googling. Maybe there is already another think tank who already debunked that or maybe there is a fact checker who already fact check that and you can easily find and verify if that is true or not. Then the other thing is how? How the content is presented? What type of photos, what kind of quotes, interviews and is there any suspicion with that? Is the headline shocking or emotional? So 95% of this information comes in negative shape in a negative sentiment. So it's quite rare to have some kind of positive disinformation. This still happens, but it's much, much less often. And the third is the circumstances when that is published, what kind of event is connected to that? So when you think about these three steps on any content piece level or news website level, this can help you to understand what's actually happening there and why. This is used by our analysts and our community of volunteers who support us with their own work and that works really, really well. We made a lot of iterations with different processes and this is one of the really, really networks well. Here is another suggestion of Global Engagement Center and this is a suggestion how to just differentiate between different sources and that also helps a lot because if it's a government funded website like Kremlin funded websites or China funded websites, there is quite big change that you need to be more vigilant and check what's happening there and analyze it better. And then when we analyze this, we publish reports of what's happening there, how much disinformation we're in different countries, what were happening on different peaks of disinformation, what kind of narratives and sub-narratives were the most popular ones during that period and time. Then also it's important to give some examples. So here's just an example from Estonia. So Estonian government increased spending on defense and the Kremlin media picked it up as increasing offense and started to spread these disinformation articles which were even 34 articles with this case. And it's a clear technique of disinformation forgery and hyper-realization in this case used. And we analyze and find many of these cases from 600 to one and a half thousand disinformation cases are found in Baltic states each month. So that's quite a lot of disinformation. So just to conclude here, what I would say is that when you want to understand this free step process, who, how and when helps a lot, then there are all kinds of community events like this one that you are participating in. This also helps a lot. You learn new things, you meet other people who can, when then you can ask them, then you can discuss and understand better what's happening. Critical thinking is one of the skills that in these days is very important. We all need to think more critically, not to get paranoid, but we really need to think more critically to understand what is happening there. One more good example is Get Bad News Game that we done in cooperation with a draw company from Netherlands and the game was tested and developed together with Cambridge University. And that game teaches citizens for six disinformation techniques. And we adopted the game, localized it in Baltic countries. And this game is a quite a big success because it increases in 15 minutes, it increases the resilience to disinformation by about 20% by the research of Cambridge. So that's quite a big result. And currently we already have 100,000 people who have played the game in Baltic countries more than 140,000 times. So that's another example how we can understand better what is happening there and how to do that at very large scale. Yes, I think that gamification of disinformation spotting and also other things, you know, like, I guess this is probably the best way out there to increase this awareness, especially on the EU because it's honestly, it's great fun and it's not only what you just mentioned, the EU versus the Zinfo also offers tests how to spot Russian disinformation in the cyberspace. And if we've got some gamers out there, you can also find related games on Steam who will help you to tell apart certain elements. This is simply amazing. And I must admit that I really do like the model that you just presented a lot because it comprises a few things that are excellent. First of all, you've got engagement of the civil society. This is indispensable. And you have employed the AI to help in your work and every practitioner knows how much information do you sometimes have to deal with when you would like to just do simple media monitoring. It's really, really a lot. And also what I like is that there is a cross-country analysis and it's really cross-border. It's simply amazing to see how it changes from country to country.