Undergraduate Course Descriptions

The aim of this course is to prepare you to work in the media business as well as to be an informed citizen by acquainting you with the work and language of media practitioners. The class also investigates the exciting, and (to some employed there) scary changes taking place in the news industry, internet industry, advertising industry, television industry, movie industry, magazine industry, and several other areas of the media system. In doing that, the course ranges over economic, political, legal, historical, and cultural considerations that shape what we see when we go online, use social media, watch TV, read books, play video games, and more. This course fulfills one of the two introductory core survey courses required of Communication majors or prospective majors. Fulfills Sector I: Society.

In this 'big data' era, presidents and popes tweet daily. Anyone can broadcast their thoughts and experiences through social media. Speeches, debates and events are recorded in online text archives. The resulting explosion of available textual data means that journalists and marketers summarize ideas and events by visualizing the results of textual analysis (the ubiquitous 'word cloud' just scratches the surface of what is possible). Automated text analysis reveals similarities and differences between groups of people and ideological positions. In this hands-on course students will learn how to manage large textual datasets (e.g. Twitter, YouTube, news stories) to investigate research questions. They will work through a series of steps to collect, organize, analyze and present textual data by using automated tools toward a final project of relevant interest. The course will cover linguistic theory and techniques that can be applied to textual data (particularly from the fields of corpus linguistics and natural language processing). No prior programming experience is required. Through this course students will gain skills writing Python programs to handle large amounts of textual data and become familiar with one of the key techniques used by data scientists, which is currently one of the most in-demand jobs.