CROSS-PLATFORM NEWS JOURNEYS: MAPPING AUDIENCE ENGAGEMENT ACROSS SOCIAL MEDIA, MESSAGING APPS, AND NEWS WEBSITES

Abstract

The proliferation of digital communication technologies has significantly transformed the way audiences discover, consume, and engage with news content. Rather than relying on a single information source, modern users navigate across multiple digital platforms, including social media, messaging applications, and dedicated news websites, creating complex cross-platform news journeys. Understanding these interconnected audience behaviours is essential for digital publishers, researchers, and policymakers seeking to improve audience engagement and optimize news dissemination strategies. This study proposes a comprehensive analytical framework for mapping audience engagement across multiple digital communication platforms by integrating behavioural analytics, audience journey reconstruction, engagement measurement, network analysis, and machine learning techniques. The proposed methodology captures user interactions from heterogeneous platforms, reconstructs chronological news consumption pathways, and analyses engagement patterns, platform transitions, and information diffusion within the digital news ecosystem. Furthermore, the framework employs network-based analysis to identify dominant navigation pathways and influential communication platforms, while predictive machine learning models evaluate audience engagement using cross-platform behavioural features. The findings demonstrate that social media platforms primarily function as gateways for news discovery, messaging applications facilitate trusted interpersonal sharing, and news websites promote deeper content engagement and audience retention. The study further reveals that effective audience engagement depends on coordinated cross-platform communication strategies rather than isolated platform optimization. By providing a unified computational approach for analysing audience behaviour, the proposed framework contributes to the fields of digital journalism, communication studies, and computational media analytics. The outcomes offer valuable insights for media organizations seeking to enhance content distribution, audience retention, and personalization, while also supporting researchers and policymakers in understanding information diffusion and digital communication dynamics within rapidly evolving news ecosystems.