Mapping AI Arguments in Journalism Studies
This work addresses the need for a clearer understanding of AI in journalism studies, but it is incremental as it focuses on categorization rather than new empirical findings.
The study tackles the problem of organizing AI concepts in journalism research by proposing a typology of seven AI subfields, aiming to provide a structured framework for scholars to analyze specific research topics more effectively.
This study investigates and suggests typologies for examining Artificial Intelligence (AI) within the domains of journalism and mass communication research. We aim to elucidate the seven distinct subfields of AI, which encompass machine learning, natural language processing (NLP), speech recognition, expert systems, planning, scheduling, optimization, robotics, and computer vision, through the provision of concrete examples and practical applications. The primary objective is to devise a structured framework that can help AI researchers in the field of journalism. By comprehending the operational principles of each subfield, scholars can enhance their ability to focus on a specific facet when analyzing a particular research topic.