Many different scientific domains are using computer-based methods and approaches to verify hypothesis or to explore possible patterns in their datasets. This course will mainly focus on text-based datasets and machine learning methods to extract both content and stylistic patterns from texts (historical documents, newspaper articles, political speeches, tweets, etc.). These datasets are typical of humanities and social sciences. Different approaches to discover the evolution over time, or the differences between authors, genders, author’s ages and their psychological profiles will be discussed.
In addition, the course will provide an introduction to basic network concepts such as density, centrality, or clustering and communities detection. Different network types will be presented to be able to evaluate hypothesis or to simulate various contagion models (e.g., epidemic, information, or fake news spreading). Applications related to the Web will be discussed.
T3 – Advanced Information Processing |
Learning outcomes The main objectives of this course is to introduce the students to the various techniques and strategies that can be used to
Jacques Savoy |
The course page in ILIAS can be found at https://ilias.unibe.ch/goto_ilias3_unibe_crs_2469215.html.
Schedules and Rooms
|Schedule||Wednesday, 08:45 - 12:00|
|Evaluation type||written exam|