One of the greatest challenges of our digital society is information overload. We are constantly required to make sense of the information coming from social media, “real” and “fake” news, the advertisement industry, or the different results for our search queries. In many cases the information we get is framed and tailored to promote obvious but also hidden aims and goals. In this course we introduce a new method for content analysis—textual network analysis—for detecting political and economic biases in the text. We first introduce the key concepts associated with the network theory, looking at various political, social, economic, technological and cultural perspectives. Then we look into a number of case study examples to illustrate aspects in the literature. Finally, we learn to use Visone, a software tool to conduct textual network analyses in order to identify the main themes in the text and its biases. As part of the course students will develop their own textual-related networks to identify the biases and framing in different texts.