Mapping AI Arguments in Journalism Studies

TL;DR

This paper develops a structured typology of AI subfields relevant to journalism studies, providing a framework to help researchers analyze AI applications within journalism and mass communication.

Contribution

It introduces a comprehensive typology of seven AI subfields with practical examples, aiding scholars in focusing their research on specific AI aspects in journalism.

Findings

Identified seven key AI subfields relevant to journalism

Provided concrete examples for each AI subfield

Created a framework to assist AI research in journalism

Abstract

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.