International Journal of Knowledge Processing Studies

Abstract The increasing frequency of road accidents highlights the urgent need for intelligent systems capable of real-time incident detection to support rapid emergency response. This paper presents a lightweight spatiotemporal accident detection framework that integrates a single-stage object detection model with an auxiliary motion-analysis stream based on dense optical flow. By jointly exploiting spatial appearance information and short-term temporal motion variations, the proposed system aims to improve robustness in complex traffic scenes while maintaining real-time performance. Unlike conventional approaches that rely solely on frame-wise object detection, the framework captures motion irregularities surrounding collision events to mitigate false alarms caused by normal traffic dynamics. A multi-source dataset was curated from publicly available traffic surveillance images and accident-related video clips obtained from heterogeneous sources, encompassing diverse viewpoints, traffic densities, and environmental conditions. The system was evaluated against representative object detection baselines using standard detection metrics, along with inference time analysis to assess deployment feasibility. Experimental results demonstrate that the proposed fusion-based approach achieves improved detection consistency with low computational overhead, making it suitable for real-time surveillance applications. The study highlights the effectiveness of combining spatial detection with simple temporal motion cues for practical accident monitoring in intelligent transportation systems, while also discussing current limitations and directions for future enhancement.

Abstract Purpose
This study investigates the structure and dynamics of entrepreneurial discourse on the Arabic Twitter (X) sphere within the Gulf Cooperation Council (GCC) states. It examines how entrepreneurship is socially constructed amidst the transition from a rentier to a knowledge-based economy, focusing on state narratives versus public sentiment.
Design/methodology/approach
Adopting a computational social science approach, the study analyzed a corpus of 48,841 content units harvested between June and December 2025. To ensure statistical independence and prevent double-voting bias, the research employed a Confidence-Calibrated Ensemble architecture. This pipeline integrates fine-tuned models (MARBERT) with pseudo-independent Large Language Model configurations (GPT-4 in zero-shot and few-shot settings) using calibrated tie-breaking. Techniques included Sentiment Analysis, Named Entity Recognition (NER), and demographic profiling of 1,888 active users.
Findings
Descriptive analysis of the collected corpus identifies Saudi Arabia as the primary discourse locus (accounting for approximately 47% of traffic). Semantic analysis reveals a significant discursive shift from economic to cultural themes, termed ‘Entrepreneurial Nationalism,’ highlighted by a substantial growth in references to state initiatives like ‘Vision 2030.’ Within this specific dataset, the ecosystem exhibits ‘fragile positivity’ (an overwhelmingly high positive-to-negative descriptive ratio), indicating a ‘spiral of silence’ regarding critical engagement. Furthermore, user profiling uncovers an ‘elite oligarchy’ dominated by middle-aged technocrats (35–49) and highly educated individuals (e.g., PhD holders), while Generation Z remains largely marginalized.
Research limitations/implications

Abstract This study seeks to identify the components of transnational knowledge as a means to enhance state–nation relations through a continuum from domestic legitimacy to international credibility, focusing on knowledge policies, requirements, and key actors. The research is applied in purpose and employs a mixed–method design. Data were collected through semi‑structured interviews with 15 experts in public administration, international relations, political science, and public policy, selected via purposive sampling. Thematic analysis was applied to the qualitative data, and a meta‑heuristic modeling approach was further used to construct a systematic model representing the relationships among key variables—such as transnational knowledge absorption capacity, knowledge policies, actor roles, domestic legitimacy, and international credibility—through structural variables and an objective function. Integrating theoretical insights and empirical themes led to the identification of six overarching dimensions shaping transnational state–nation relations: (1) international stakeholders and state legitimacy; (2) global economic integration and competitiveness; (3) cultural, scientific, and media diplomacy; (4) global governance and transnational accountability; (5) international responsiveness to global public interests; and (6) transnational actors and civil society engagement. Together, these dimensions formed a comprehensive network of requirements, actors, and influencing factors for improving state–nation relations. The findings indicate that strengthening state–nation relations requires a shift from purely domestic approaches toward multi‑level and transnational governance. International legitimacy, economic integration, active cultural diplomacy, and engagement with transnational actors constitute the core elements of this transformation.

Abstract Information disorder, as one of the main challenges of the digital age, leads to the formation of repeated and repeated information seeking behaviors, known as Extra-informationalism. This phenomenon is the result of a complex interaction between four main components: sender, content, channels and receivers. Senders with political, economic and ideological motives, along with the use of opaque actors and the production of content based on artificial intelligence, try to manipulate public perception. Information content, with its inaccurate, emotional, complex and multimedia characteristics, increases cognitive load and ambiguity and leads audiences to repeatedly search for information. Digital channels, including content personalization algorithms and weaknesses in information monitoring and governance, facilitate the rapid and pervasive spread of disruptive information. Receivers are also more likely to be caught in the cycle of Extra-informationalism due to weaknesses in information and media literacy, cognitive biases and emotional and psychological states. Qualitative data analysis with MAXQDA software showed that these factors simultaneously reinforce multi-source and frequent search behaviors. The findings highlight the importance of designing information literacy programs, promoting digital well-being, and formulating effective policies on information governance, and provide a conceptual framework for understanding the mechanisms that create Extra-informationalism.