[MUSIC] Hello everyone, welcome to the first class. We will talk about the research and the intersection of data science and international relations. And we will start by defining big data, since it's a key object of the research. There are many approaches towards the definition of big data. Some people define big data by looking at data itself. They differentiate big data from small, normal or large data in relation to the size of the data set. However, the size of the data set might not be a sufficient indicator. That is why people explore other tributes of big data. For example, it's heterogeneous characteristics, which means that data are big if they are first generated automatically in real-time, and second, semi-structured or unstructured, third, it cannot be processed and analyzed with traditional tools. Also, big data is often referred in relation to widely quoted V's originally proposed by Laney in 2001. Laney put forward three elements to describe big data, volume, the size of the datasets, velocity, the speed at which big data is generated, and variety, the many different forms that big data takes. Later this definition was updated with the force field, veracity, the complexity is related to the analysis of big data and related questions of a characteristic. So, people consider big data according to the kind of analysis that is performed on them, razors and looking at the characteristics of the data set. They look at the new kind of information and knowledge that that can be produced. On this table you see a comparison of big data and small data according to 3 V's. The volume of big data is calculated in petabytes, which means 10th to 15th degree bytes of digital information. This is a lot of data. On the contrary, volume of small data is low. Big data are generated in real-time whereas small data relates to batch processing, where you work with a file. Finally, as we previously discussed, big data are semi-structured or unstructured while small data are always structured. If we imagine that big data is an iceberg, than small data is what is above the water. That is, we ourselves separated small data from big data and structured it with regard to our research goals. Small data is what we are able to see and analyze. The definition adopted by the Oxford English online dictionary attempts to merge both approaches. Where members that they are big data by looking at data itself, and big data is type of analysis. And defines big data as extremely large datasets that may be analyzed computationally to reveal patterns, trends and associations, especially relating to human behavior and interactions. So we have smoothly approach data science. Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural an unstructured data. In fact, it lies in the intersection of three areas, mathematics, computer science and domain expertise. In our case, domain expertise is the field of international relations. Data science is a concept that covers the entire scope of data collection and processing. The question that we should ask ourselves in this regard is, how does the possibility of studying data affect the field of international relations? I will name three trends through which it is easier to realize this. First trend is datafication revolution, which means that the huge growth of datafication and big data analytics are revolutionizing the way we see and process the world. The significance of this phenomenon is comparible to the appearance of Gutenberg printing press in the 15th century. Second trend is recombinant data, meaning that causality is being replaced by correlation. This means that potential of data analysis studies lies in the capacity of big data to detect certain patterns in human behavior. Thus the third trend follows from this, randomization makes us closer to reality, that did our dependence on small data and accuracy. To conclude, the possibility of studying data affects the field of international relations by making the research in this field more diverse and deeper. And then expected results allows to look at many ordinary processes and well known concepts from a new angle. An infinite amount of data can reveal those patterns in international relations previously hid from a human researcher, but which can be discovered by researcher using computer technology. A little joking, we can say that big data plus the super abilities of our brain is smart data, a great data. That is the data that we get as a result of our analysis. Small data allow us to draw conclusions. So at the end of our class, let's repeat all data types on the example of this abstract of our paper about international Twitter discussion about Syria. All tweets about Syria on Twitter, they're hundreds of millions, are big data. We need it for analysis, only the most influential ones. We applied some specific measures and retrieved small data from general picture provided by big data. Having carefully analyzed them, we found some important patterns. In other words, got our smart data, which allowed us to make a conclusion.