Evaluation of Government Performance in the Context of Social Media Filtering

Purpose: Social network filtering is implemented in many countries for various reasons, including combating cybercrimes, preventing the spread of rumors, and curbing the promotion of violence, immorality, and other forms of inappropriate content. Governments often justify these policies as a way to protect national security, maintain social order, and safeguard cultural values. However, one of the most significant challenges of filtering is the lack of systematic evaluation of government policies in this area. Without proper evaluation, it becomes difficult to determine whether the policy achieves its intended objectives or creates unintended negative consequences, such as economic costs or reduced trust in governance. Therefore, this study aimed to evaluate the government's performance in filtering social networks comprehensively.
Design/ methodology/ approach: Based on the defined objectives, the research is classified as applied research, as it seeks to address a practical policy issue. In terms of data collection, it falls under descriptive-survey research; and regarding the nature of the data, it is categorized as mixed-methods research, combining both qualitative and quantitative dimensions to ensure a more reliable and valid outcome. Data were collected through semi-structured interviews designed to explore expert opinions in depth while allowing flexibility to capture unexpected insights. The study population included academic experts in management and information technology, government managers in communications, and specialists in communications and IT. The sampling method was non-random purposive sampling, which enabled the researchers to deliberately select individuals with relevant knowledge and expertise. The researchers conducted 15 interviews until theoretical saturation was achieved. The semi-structured interviews were analyzed using the Attride-Stirling thematic analysis method, which provides a systematic process for identifying, analyzing, and reporting patterns within qualitative data. Additionally, the Interpretive Structural Modeling (ISM) method was used to structure and prioritize the identified factors by influence and interrelationships.
Research Findings: The analysis of factors affecting the efficiency, effectiveness, and public acceptance of the Iranian government’s social media filtering policy shows that the policy's success largely depends on institutional coordination, strong technical infrastructure, and public trust. Regarding efficiency, technical infrastructure, institutional coordination, and continuous monitoring are critical factors at the first and second levels, ensuring effective policy implementation. At the third level, resource allocation and private-sector cooperation are highlighted as key drivers. In terms of effectiveness, achieving goals such as reducing illegal content and influencing user behavior falls at the first level, while challenges like access to filter-bypass tools and cybersecurity issues fall at the second level. Institutional coordination is emphasized as an independent and influential factor across all levels. For public acceptance, the quality of domestic platforms, public awareness campaigns, and government transparency stand at the first level, whereas broader issues such as the impact on access to information and livelihoods appear at lower levels. The findings suggest that these interrelated factors form a complex network of interactions, in which institutional coordination emerges as a pivotal element that can strengthen policy coherence, infrastructure, and transparency and, in turn, enhance all three dimensions simultaneously.
Limitations & Consequences: In the present study, time constraints prevented testing the obtained models, which could have further validated the results. Another limitation was the lack of a detailed examination of the dynamic relationships between the identified factors. Nevertheless, this research has significant implications. The findings suggest that policymakers can enhance the success of filtering policies by focusing on institutional coherence, strengthening technical infrastructure, and promoting transparency and public participation.
Practical Consequences: Evaluating government performance on social media filtering in terms of efficiency, effectiveness, and public acceptability provides a practical tool for improving policymaking. Such evaluation can reduce social and economic harms, increase accountability, and foster positive interaction between the government and the public.
Innovation or value of the Article: One innovative aspect of this research is its use of a three-dimensional framework—efficiency, effectiveness, and public acceptability—to evaluate the Iranian government’s performance on social media filtering. While many previous studies have addressed the effects of filtering in a fragmented, isolated manner, this study combines the three perspectives, offering a comprehensive, multidimensional analysis. This holistic approach not only enriches academic understanding but also offers practical guidance for policymakers seeking balanced, sustainable solutions.
Paper Type: Original Paper