Down to a r/science
PDF

Keywords

social network analysis, source credibility, science communication, social media, expertise

How to Cite

Hubner, A., McKnight, J., Sweitzer, M., & Bond, R. (2021). Down to a r/science. Computational Communication Research, 3(1), 91-115. Retrieved from https://computationalcommunication.org/ccr/article/view/33

Abstract

Digital trace data enable researchers to study communication processes at a scale previously impossible. We combine social network analysis and automated content analysis to examine source and message factors’ impact on credibility ratings. We found that the expertise of the author, the network position that the author occupies, and characteristics of the content the author creates have a significant impact on how that content will be assessed by others.  By observationally examining a large-scale online community, we provide a real-world test of how source and message characteristics are evaluated by message consumers. Our results show that it is important to think of online communication as occurring interactively between networks of individuals, and that the network positions people inhabit may inform their behavior.

PDF
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.