# Mapping AI Arguments in Journalism Studies

arXiv: https://arxiv.org/abs/2309.12357 · HTML: https://mlsanity.com/paper/2309.12357/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 24 references that are in the map.
- First posted on arXiv 3 Sep 2023.

## Builds on (most cited first, 1 of 1)

- [ChatGPT is not all you need. A State of the Art Review of large Generative AI models](https://mlsanity.com/paper/2301.04655/) (2023)

## Abstract (arXiv)

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.