Computational Journalism

Computational journalism is the interpretation of journalistic knowledge in ways that are accessible to algorithmic computation. Journalism interpreted this way can enable new techniques for gathering, producing, and distributing journalism, or it deliver audience experiences not possible when solely as unstructured natural language. The application computational approaches has emerged opportunistically from practice within newsrooms, often using technologies originating other disciplines industries, therefore characterized a field by wide variety techniques, projects, products without obvious theoretical underpinnings. newsrooms primarily been concentrated three broad categories automation augmentation; news gathering at scale, production artifacts, personalized distribution consumers. Other kinds such computationally enabled conversational agents interactive experiences, immersive more visceral news, have also received attention scholars but proven less sustainable newsrooms. interventions ecosystem, with automated forms fact-checking monitoring misinformation disinformation yet demonstrated utility routine operation. Academic scholarship computation largely followed trajectory emergence practice. Early work focused on describing exotic adjuncts traditional journalism. As influence grew, efforts were made organize varied expressions into coherent categorization schemes. Later recognized potential effect disruptive change thus became its impact audiences journalists. A small dispersed technical literature directed exists, partially communication studies, computer science, data related fields. journalism’s occurred context growing existential threat business models effects ubiquitous networked communication. portrayed, scholarship, response threat.