The production and spread of digital news involves a wide range of actors: journalists and the organizations that employ them, social media platforms, audiences, and myriad commentators, citizen journalists, bloggers, and other actors who contribute to the news ecosystem without inhabiting an official role. These actors interact in flexible, often unexpected ways. Because of the range of actors involved, the dynamic nature of their activity, and the ways in which they interact, the disparate parts constituting digital news media are difficult to encapsulate under one unified framework. In this work, I argue for an approach to studying news media at the system level. Building on existing theories of digital journalism, I advocate for a paradigm that embraces the networked nature of news. In this view, it is counterproductive to examine news actors or processes in isolation, as it is their connections to other parts of the media system that make them consequential. To motivate this view, I draw on concepts from the study of complex systems, with a particular focus on interconnectedness and emergence. I demonstrate how these concepts can be integrated with ongoing theoretical developments in the field of communication, providing a generative toolset for understanding the complexity of digital news. This dissertation includes four studies that embrace this complexity-oriented paradigm in empirical settings. In each, I identify a subset of actors and the relationships among them, then demonstrate how those relationships impact other parts of the larger media system. Taken together, these studies offer insight into the myriad indirect influences that shape news production, distribution, and consumption. They also offer guidance on potential strategies for navigating unpredictability in empirical processes. Finally, they outline key methodological considerations for the large-scale study of digital systems. I end by discussing implications of this work and its potential applications in future research.

Creator

• Hagar, Nicholas

DOI

• https://doi.org/10.21985/n2-yqac-pr59

Subject

• Journalism
• Computer science
• Communication

Language

• en

Alternate Identifier

• etdadmin_upload_984386
• http://dissertations.umi.com/northwestern:16531

Keyword

• computational social science
• algorithms
• digital journalism
• simulation
• network analysis
• complexity

Date created

• 2023-01-01

Resource type

• Dissertation

Rights statement

• In Copyright