AI vs Human News Headlines: A Comparative Study of Syntax and Emotional Language

Abstract

This research examines the comparative linguistic features of newspaper headlines produced by artificial intelligence systems versus human journalists, concentrating particularly on grammatical structure and affective language use. Utilizing theoretical frameworks from Systemic Functional Linguistics, News Values Theory, and Critical Discourse Analysis, the study employs comparative content analysis methodology to evaluate paired headlines sourced from traditional news organizations (BBC, NBC) and AI news platforms (NewsGPT.ai). Results indicate that AI-produced headlines tend to be more concise, declarative, and sensationalized, utilizing active constructions and event-focused verbs. Conversely, human-crafted headlines exhibit greater length, explanatory depth, and analytical perspective, incorporating narrative contextualization, emotional engagement through stylistic devices, and direct quotations. Human-authored content additionally shows enhanced numerical specificity and grammatical intricacy, whereas AI-generated headlines prioritize compression and factual documentation. The research determines that although AI demonstrates capability in generating efficient and striking headlines, human journalists remain essential for maintaining precision, contextual richness, and empathetic authenticity. These results underscore the necessity for harmonious collaboration between AI and human contribution in digital journalism, as each approach offers distinctive yet mutually reinforcing capabilities to modern news media.