Artificial Intelligence and Journalism: A Systematic Bibliometric and Thematic Analysis of Global Research

2025-07-14

AI Summary

This study systematically examines the multidimensional impacts of artificial intelligence on global journalism and its associated ethical, professional, and societal challenges. Following the PRISMA 2020 guidelines, we conducted a bibliometric review of peer-reviewed literature (2010–2025) from Scopus and Web of Science, integrating quantitative bibliometric analysis, LDA-based topic modeling, and VADER sentiment analysis—marking the first study to jointly quantify research landscapes and assess affective orientations toward AI in journalism. Results indicate a sharp post-2020 surge in publications, concentrated on automated content production, disinformation mitigation, and algorithmic accountability. Knowledge production remains heavily skewed toward North America and Europe, with pronounced underrepresentation from the Global South. Overall sentiment is cautiously optimistic; however, concerns regarding algorithmic bias, opacity, and regulatory gaps are intensifying. The findings provide empirical grounding and policy-relevant insights for fostering an inclusive, transparent, and ethically robust AI-integrated news ecosystem.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy
• Machine Learning: Ethics, Bias, and Fairness

Application Category

• Web Mining and Content Analysis: Web data quality in the era of algorithmically-generated content
• Social Networks and Social Media: Fairness and bias in social network and social media analysis
• Semantics and Knowledge: Provenance, trust, security and privacy, and ethical issues in managing semantic data

Abstract

Artificial Intelligence (AI) is reshaping journalistic practices across the globe, offering new opportunities while raising ethical, professional, and societal concerns. This study presents a comprehensive systematic review of published articles on AI in journalism from 2010 to 2025. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, a total of 72 peer-reviewed articles were selected from Scopus and Web of Science databases. The analysis combines bibliometric mapping and qualitative thematic synthesis to identify dominant trends, technologies, geographical distributions, and ethical debates. Additionally, sentiment analysis was performed on article abstracts using the Valence Aware Dictionary and sEntiment Reasoner (VADER) algorithm to capture evaluative tones across the literature. The findings show a sharp increase in research activity after 2020, with prominent focus areas including automation, misinformation, and ethical governance. While most studies reflect cautious optimism, concerns over bias, transparency, and accountability remain persistent. The review also highlights regional disparities in scholarly contributions, with limited representation from the Global South. By integrating quantitative and qualitative insights, this study offers a multi-dimensional understanding of how AI is transforming journalism and proposes future research directions for inclusive and responsible innovation.

Problem

• Analyzes AI's impact on journalism practices globally
• Identifies trends in AI journalism research from 2010-2025
• Examines ethical concerns and regional disparities in AI journalism

Innovation

• PRISMA 2020 guidelines for systematic review
• Bibliometric mapping and thematic synthesis
• VADER algorithm for sentiment analysis