Analysis of Audience Trust in Digital Communication on Social Media

Sari Ningsih; Taufik Permadi; Utami Hermawan

Authors

Sari Ningsih Universitas Padjadjaran Author
Taufik Permadi Universitas Padjadjaran Author
Utami Hermawan Universitas Negeri Surabaya Author

Keywords:

Audience trust, Digital communication, Social media, Misinformation, Digital literacy

Abstract

This study aims to analyze audience trust in digital communication on social media, particularly in the context of the increasing flow of information, misinformation, and uncertainty regarding the credibility of sources in the digital space. This study employs a qualitative approach with a phenomenological design to understand the subjective experiences of audiences in evaluating, questioning, and validating the information they receive through social media. Data were collected through semi-structured interviews, non-participatory digital observation, and documentation of communication activities on several social media platforms. Research participants consisted of active social media users selected purposively based on the intensity of their usage, their experience accessing digital information, and their involvement in evaluating or sharing information. The research findings indicate that audience trust is shaped by six main themes: source credibility, repeated interaction experiences, community social validation, emotional closeness, self-verification strategies, and awareness of the role of algorithms. These findings demonstrate that digital trust is not solely determined by the quality of information but also by social relationships, personal experiences, community dynamics, and platform structures. This study contributes to the development of digital communication research by positioning audience trust as a dynamic and multidimensional negotiation process. The research implications emphasize the importance of transparent, responsive, and evidence-based digital communication, as well as the strengthening of digital literacy that encompasses understanding of bias, emotions, the ethics of information sharing, and algorithms.

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