This study aims to examine how algorithmic agenda-setting and user-generated content influence are associated with political cognition and civic engagement in social media environments. Grounded in second-level agenda-setting theory and a knowledge management perspective, it develops and tests a framework linking algorithmic curation and participatory content with issue salience perception, framing persuasion strength, agenda fragmentation awareness and civic engagement intention. The study considers social media as an algorithmically mediated digital knowledge environment and examines how civic knowledge becomes visible, shared, prioritized, interpreted and translated into intended action.
The study adopts a quantitative research design using survey data collected from 295 social media users in the USA and the UK. Measurement items were adapted from established scales and assessed using a five-point Likert scale. The proposed conceptual model, comprising six constructs, was tested using partial least squares structural equation modeling (PLS-SEM) through SmartPLS 4. Reliability, validity and common method bias were assessed before testing the direct and serial indirect relationships. The analysis included both direct and serial mediation effects to evaluate the relationships among algorithmic agenda-setting, user-generated content influence, issue salience perception, framing persuasion strength, agenda fragmentation awareness and civic engagement intention.
The findings show that algorithmic agenda-setting and user-generated content influence are positively associated with issue salience perception, which is subsequently associated with framing persuasion strength. Framing persuasion strength is positively related to both agenda fragmentation awareness and civic engagement intention. Significant serial indirect effects were also found, indicating that the associations of algorithmic and user-driven content with civic outcomes occur through issue salience and framing. From a KM perspective, the results show how civic knowledge progresses from visibility and participatory sharing to prioritization, interpretation, fragmentation awareness and intended action.
The study is limited by its focus on respondents from the USA and UK, restricting generalizability to other cultural and technological contexts. The use of cross-sectional and self-reported data limits causal inference and may introduce response biases. Additionally, key constructs were treated as unidimensional despite their conceptual complexity. Future research should adopt longitudinal or experimental designs, incorporate behavioral data, and explore moderating variables such as political orientation and digital literacy. Despite these limitations, the study contributes a process-based KM explanation of how algorithmic curation and user participation shape the visibility, prioritization, interpretation and use of knowledge in digital environments.
The study provides actionable insights for platform designers, policymakers and civic organizations. It highlights the need for transparent and explainable algorithmic curation to help users understand how political content is prioritized. Civic engagement strategies should leverage user-generated content and participatory storytelling to enhance issue salience. Additionally, civic communicators should use credible, clearly framed, and action-relevant messages while avoiding manipulative or polarizing appeals. The findings also emphasize the importance of media literacy initiatives to help users critically evaluate persuasive content and mitigate the effects of fragmentation. Overall, interventions should address the full cognitive-affective pathway to foster meaningful and informed civic engagement in digital environments.
The study underscores the societal impact of algorithmic and participatory media in shaping political awareness and engagement. It shows that digital platforms may support civic participation while also being associated with fragmented public discourse. By highlighting the role of framing and salience, the research emphasizes the need for more inclusive, transparent and responsible digital communication ecosystems. The findings advocate for strengthening digital literacy and fostering critical engagement among users to counter polarization and misinformation. Ultimately, the study contributes to broader societal efforts aimed at enhancing democratic participation, promoting informed citizenship and addressing the challenges of fragmentation in the digital public sphere.
This study contributes to KM by conceptualizing social media as an algorithmically mediated digital knowledge environment rather than only as a communication channel. It explains how algorithmic curation and user participation are associated with the visibility and sharing of civic knowledge, while issue salience and framing support its prioritization and interpretation. The serial indirect pathways further show how these knowledge processes are linked with fragmentation awareness and civic intention. The process is also relevant beyond political communication, as platform algorithms and user participation may similarly shape knowledge visibility, legitimacy and use in organizations, online communities and public-service settings.
