Bibliometric and Content Analysis of the Scientific Work on Artificial Intelligence in Journalism

新闻 工作(物理) 内容(测量理论) 内容分析 文献计量学 数据科学 计算机科学 工程伦理学 社会学 媒体研究 社会科学 图书馆学 工程类 数学 机械工程 数学分析
作者
Alem Febri Sonni,Vinanda Cinta Cendekia Putri,Irwanto Irwanto
出处
期刊:Journalism and media [MDPI AG]
卷期号:5 (2): 787-798 被引量:1
标识
DOI:10.3390/journalmedia5020051
摘要

This paper presents a comprehensive bibliometric review of the development of artificial intelligence (AI) in journalism based on the analysis of 331 articles indexed in the Scopus database between 2019 and 2023. This research combines bibliometric approaches and quantitative content analysis to provide an in-depth conceptual and structural overview of the field. In addition to descriptive measures, co-citation and co-word analyses are also presented to reveal patterns and trends in AI- and journalism-related research. The results show a significant increase in the number of articles published each year, with the largest contributions coming from the United States, Spain, and the United Kingdom, serving as the most productive countries. Terms such as “fake news”, “algorithms”, and “automated journalism” frequently appear in the reviewed articles, reflecting the main topics of concern in this field. Furthermore, ethical aspects of journalism were highlighted in every discussion, indicating a new paradigm that needs to be considered for the future development of journalism studies and professionalism.

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