Communication Strategies and Effects of Public Policy Advocacy on Social Media Platforms: A Mixed-Methods Analysis of Framing, Engagement, and Policy Influence
DOI:
https://doi.org/10.63808/pcm.v2i4.413Keywords:
Public policy advocacy, Social media, Framing theory, Digital engagement, Networked publics, Political communication, Content analysisAbstract
In this paper we examine the use of framing by advocacy organizations and government entities in social media to advance public policy goals and the effect of those strategies on different types of citizen response. We adopt a sequential explanatory mixed methods design by combining quantitative content analysis of a 2340-policy related posts from Twitter/X, Facebook, and Instagram with semi-structured interviews of 24 communication professionals. The sample comprised 20 public-facing organizations operating in one national context, in four policy domains – healthcare, environmental policy, education and social welfare. Five framing categories – diagnostic, prognostic, motivational, episodic, and thematic – were operationalised and evaluated against publicly available engagement metrics (likes/reactions, shares/reposts and comments), while click-through rate was evaluated separately where organisation-level analytics were accessible. Motivational framing generated more total engagement, but episodic framing generated more substantive comment-based participation. Differences across platforms demonstrate that predominantly visually-oriented environments support motivational and narrative frames, and platforms with more supports for text and links support solution-oriented and deliberative policy talk. According to interview results, we can explain this pattern by an engagement – depth paradox: Practitioners need attention maximizing content and at the same time want to be able to express complex policy positions in a responsible way. The study is a contribution to research on digital political communication, in bringing together framing strategies, platform affordances, algorithmic uncertainty and various modes of engagement for policy advocacy.
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