Journalists’ Lived Experiences of Credibility and Ethical Identity in the Digital News Era
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Abstract
Digital journalism has undergone a profound transformation as algorithms and audience engagement metrics increasingly shape how news is produced and perceived. Within this evolving media landscape, the concept of journalistic credibility has shifted from being an institutional guarantee to a dynamic and contested experience shaped by technological and social forces. However, little is known about how journalists personally experience and interpret credibility crises in the digital newsroom, particularly as they navigate tensions between ethical responsibility and algorithmic visibility. This study applies an interpretative phenomenological approach (IPA) to explore the lived experiences of journalists confronting these challenges and to uncover the meaning structures underlying their sense of professional integrity. The study employed clearly defined IPA procedures, including bracketing, idiographic coding, and cross-case thematic synthesis, to ensure methodological rigor. Data were collected through semi-structured interviews with twelve journalists from print, electronic, and digital media. Analysis identified three core experiential themes: (1) credibility as an ongoing ethical struggle shaped by algorithmic pressures, (2) emotional vulnerability triggered by fluctuating digital visibility, and (3) the negotiation of professional identity amid demands for authenticity. These findings demonstrate with greater precision that credibility is experienced not as an abstract principle but as a daily moral decision-making process shaped by both personal conviction and platform metrics.These insights extend the theoretical understanding of credibility from a procedural construct to a lived moral condition, emphasizing the human dimension of journalistic practice in the digital age. The study offers new directions for research on media ethics and underscores the need for reflective newsroom cultures that sustain authenticity amid algorithmic systems.
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