Entrepreneurship Discourse in the Arabic Twitter Sphere: A Sentiment and Content Analysis

PurposeThis 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 ۴۸,۸۴۱ content units harvested between June and December ۲۰۲۵. 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-۴ in zero-shot and few-shot settings) using calibrated tie-breaking. Techniques included Sentiment Analysis, Named Entity Recognition (NER), and demographic profiling of ۱,۸۸۸ active users.Findings Descriptive analysis of the collected corpus identifies Saudi Arabia as the primary discourse locus (accounting for approximately ۴۷% 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 ۲۰۳۰.’ 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 (۳۵–۴۹) and highly educated individuals (e.g., PhD holders), while Generation Z remains largely marginalized.Research limitations/implications

کلیدواژه ها:

Entrepreneurship ، Sentiment analysis ، Arabic Twitter ، Data mining ، Vision ۲۰۳۰