Artificial Intelligence

Presentation Online social networks and social media play a central and growing role in our daily life. They influence how we communicate with our friends, how we obtain and consume media and news content, how we apply for a job, even how the information we look up in Wikipedia is generated or how political parties try to convince you to vote for them. The aim of this course is to provide both the theoretical background as well as the practical tools to analyse, model and visualize the multiple facets of these phenomena. The course provides an overview about the state of the art in Social Network Analysis and how its metrics have been derived from theories in Sociology. Furthermore, it will provide knowledge about tools and methods to derive specific social media datasets and the way to visualize social networks that go beyond an ugly hair ball of nodes and edges. Finally, it will cover more advanced topics such as learning and inference, information diffusion, community structure and prediction. Associated skills Basic Competences That students have and understand knowledge that provides a basis or opportunity to be original in ○ the development and/or application of ideas, often in a research context. That students know how to apply the acquired knowledge and their ability to solve problems in new or little-known environments within broader (or multidisciplinary) contexts related to their area of study. That students are able to integrate knowledge and face the complexity of making judgments from information that, being incomplete or limited, includes reflections on the social and ethical responsibilities linked to the application of its knowledge and judgments. That the students know how to communicate their conclusions and knowledge and ultimate reasons that support them to audiences specialized and non-specialized in a clear way and without ambiguities. That students possess the learning skills that allow them to continue studying in a way that will be largely self-directed or autonomous. Specific Competences Identify novel applications of models and algorithms in the field of interactive intelligent systems. Ability to communicate effectively using the technical vocabulary of the field in English. Apply machine learning models and algorithms to a well-identified interactive intelligent systems problem. Learning outcomes Ability to apply and identify basic algorithms in social networks modeling, analysis, and visualization. Ability to read and demonstrate good comprehension of scientific articles in the area of data-driven social analytics. Identify parallels in problems in the field of interactive intelligent systems.