This research seminar offers an overview of the emerging field of computational communication including a sampling of methods for computational modeling, content analysis, network analysis, and simulation of communication-oriented data, as well as the application of critical approaches, and the empirical study of computational communication systems mediated by algorithms and AI. Through engagement with the latest scholarship in the field, the emphasis of the course is not on methodological mechanics, but rather on developing conceptual, strategic, and critical thinking to assess opportunities that computational methods and computational advances in society create for communication research. Here's the Syllabus
Algorithmic News Media
The increasing role that algorithms and automation are playing in the production of information is rapidly changing the ways in which the news media is authored, curated, disseminated, and consumed. This graduate seminar provides an overview of the latest developments in algorithmic news media on topics including journalistic data mining, automated content production, news bots, platform dissemination, and algorithmic accountability and transparency. Themes of value-sensitive design, labor, and sustainability are discussed with respect to how algorithms impact the public sphere. Here's the Syllabus
This course explores the conceptualization and application of computational and data-driven approaches to journalism practice. Students examine how computational techniques are changing journalistic data gathering, curation, sensemaking, presentation, dissemination, and analytics of content. Here's the Syllabus.
Storytelling with Data Visualization
This course covers the use of data visualization as a method to communicate news stories (narrative visualization) and as a way to explore and analyze data as a method to find new news stories (visual analytics) in a journalism context. Here's the Syllabus