Abstract
Technological developments in the last decades have fundamentally transformed the news industry and the way citizens interact with media. Personal computers and smartphones abound, and internet has become the most common way citizens access news. Social media platforms and search engines have become both gateways and gatekeepers for finding and accessing content, their algorithms routinely relied upon for distributing stories. Online, news competes for attention with a flood of content. The move online presents remarkable opportunities for both studying and influencing news behaviors. But despite growing online audiences and the promises of methodological advancements, news companies are struggling to adapt to the new reality they have come to find themselves in. This thesis offers new insights into what online news behaviors of both humans and algorithms look like empirically and illustrate how those can be studied. The dissertation consists of five original research studies which explores methods and patterns in online news activity. The studies cover several aspects of online news behavior, such as distribution and consumption of news content and the effectiveness of presenting advertising on news websites. The thesis also presents a theoretical position explaining the changes we see in news behaviors and offers a suggested path for news media going forward; focus on function over content when deciding what and how to publish. The thesis has important implications for news professionals, media researchers, and practitioners working with online behaviors.