Applying Social Media Data in Science and Technology Policy Agenda-Setting (A Case Study: Platform X)

Objective
Although a growing body of international literature has examined the role of social media in agenda-setting processes, public opinion formation, and intermedia agenda-setting, there remains limited empirical research on how social media data can be systematically employed within the policy agenda-setting stage of science and technology policymaking. In the Iranian context, this gap is particularly pronounced. While social media platforms, especially X (formerly Twitter)—have become highly politicized spaces where policy-relevant debates unfold, policymakers lack clear frameworks, methods, and empirical evidence to guide the use of such data in policy agenda-setting.
The central problem addressed in this study is the lack of clarity regarding how social media data, and more specifically influential user-generated posts, can contribute to agenda-setting in science and technology policy. Existing studies often focus on media effects, public opinion dynamics, or intermedia relationships between traditional and social media, but they rarely translate these insights into concrete implications for policy agenda-setting. Consequently, policymakers face uncertainty about which types of social media content matter, which actors exert influence, and which characteristics of posts enable them to shape policy priorities. The primary objective of this study is to examine how social media user data can be utilized in the agenda-setting stage of science and technology policymaking. More specifically, the research seeks to identify the content-related and structural characteristics of influential posts on the X platform that possess agenda-setting capacity in the context of technology policy. To achieve this objective, the study addresses the following overarching research question: How can social media data be used to inform and support agenda-setting in science and technology policymaking? This question is further operationalized through a focused empirical investigation of a salient policy event: the proposal of the “User Protection in Cyberspace Plan” in Iran. By examining how this policy issue emerged, circulated, and gained prominence on X, the study aims to uncover the mechanisms through which influential posts contribute to policy agenda-setting.
Research Methodology
The study is grounded in agenda-setting theory, originating from the seminal work of McCombs and Shaw, which demonstrated the capacity of mass media to shape public perceptions of issue salience. Subsequent developments in agenda-setting research extended the framework to intermedia agenda-setting, highlighting how different media platforms influence one another. With the rise of social media, scholars have increasingly examined agenda-setting dynamics between traditional media and digital platforms, as well as the role of user-generated content in shaping issue salience. Building on this literature, the present study situates social media platforms—specifically X—as arenas where agenda-setting processes unfold not only through institutional media actors but also through influential users. By focusing on the agenda-setting stage of the policy cycle rather than the entire policymaking process, the study narrows its analytical scope to the early phase in which issues gain attention and enter the policy agenda.
This research adopts an exploratory qualitative approach. The study begins with a systematic review of prior research on social media data usage, agenda-setting, and policy-related communication. This review informs the conceptual framework and guides the empirical analysis. Empirically, the study focuses on a single, high-profile technology policy event: the “User Protection in Cyberspace Plan.” Data was collected from the X platform over a one-year period surrounding the emergence and discussion of this policy proposal. Influential posts were identified based on an operational definition specified in the methodology section, incorporating engagement metrics and indicators of visibility. The selected posts were subjected to qualitative content analysis and thematic analysis. This dual analytical approach enabled the identification of recurring themes, discursive patterns, and salient features within influential posts. The analysis distinguishes between content-related characteristics—such as linguistic features, emotional tone, thematic emphasis, temporal dynamics, and frequency patterns—and structural characteristics, including user account attributes (e.g., number of followers, account age, and profile features).
The choice of the X platform is motivated by its distinctive affordances and its prominent role in political and policy-related discourse in Iran. Despite long-standing filtering, X continues to host a substantial and politically engaged user base in the country, including policymakers, experts, journalists, and technology companies. The platform’s emphasis on topical content, hashtags, and algorithmic timelines facilitates rapid issue amplification and public debate, making it particularly suitable for agenda-setting analysis. The “User Protection in Cyberspace Plan” was selected as the empirical case due to its significance within Iran’s technology policy landscape and its high visibility on X. The issue generated intense debate, mobilized diverse actors, and appeared to influence policy discussions and implementation strategies, rendering it an appropriate case for examining agenda-setting dynamics.
Findings
The findings reveal that influential posts on X exhibit a combination of content-related and structural features that enhance their agenda-setting potential in science and technology policymaking. Content-wise, posts with strong emotional framing, clear and accessible language, and explicit policy relevance were more likely to gain visibility and engagement. Temporal factors, such as timing of publication relative to key policy developments, also played a significant role. Structurally, posts originating from accounts with high follower counts, established credibility, and strong network connections demonstrated greater influence. Interaction patterns, including retweets, replies, and mentions, further amplified the visibility of certain posts, contributing to the sustained prominence of the policy issue. Together, these features facilitated the transformation of individual posts into focal points of collective attention, thereby shaping the policy agenda.
Discussion & Conclusion
This study demonstrates that social media data—particularly influential posts on the X platform—constitute a valuable resource for identifying priority issues and understanding agenda-setting processes in science and technology policy. By focusing on the agenda-setting stage, the research highlights how specific characteristics of social media posts contribute to issue salience and policy relevance. The findings suggest that policymakers can benefit from systematically monitoring and analyzing influential social media content to better understand emerging concerns and societal sensitivities. More broadly, the study provides a foundation for developing data-driven tools and frameworks that integrate social media analytics into policy agenda-setting processes. Such approaches hold promises for enhancing policy responsiveness, inclusiveness, and contextual awareness in science and technology governance.