To Interact or Not to Interact with News Posts: The Role of Algorithmic Awareness & Self-Monitoring in Facebook News Consumption

Abstract

While algorithms govern our newsfeed on social networking sites, most studies have sought to explore conditions to encourage audience interaction with news content. Few, however, have examined how audiences may refrain from content interaction which provides key indicators for news organizations gauging content impact and reflects online civic engagement. Through the theoretical lens of self-presentation and hyperpersonal model, this study examines the role of algorithmic awareness and self-monitoring in SNS news consumption. Using an online survey of Facebook news consumers (N = 808), findings reveal an association between algorithmic awareness, self-monitoring, and active news consumption on Facebook. The mediating role of self-monitoring indicates that levels of algorithmic awareness encourage active consumption when the stakes for self-presentation on the platform are high. Differences in algorithmic awareness levels by gender, age, and education are identified. The study provides promising preliminary evidence on how algorithmic awareness impacts SNS news consumption and practical implications for practitioners.

Keywords

algorithmic awareness self-presentation hyperpersonal model social networking sites active news consumption

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