In contemporary geopolitical crises, digital platforms have transformed from neutral communication tools into active infrastructures of “algorithmic governance” and the main battlefield of narrative warfare. During the Iran-Israel military tensions, Platform X played a pivotal role in shaping public opinion. Applying a computational social science approach, this study dissects how algorithms function in shaping the flow of information. Accordingly, 30,000 enriched data records (filtered from 120,000 raw data) were analyzed in three time phases: pre-crisis (T0), crisis peak (T1), and post-crisis (T2) using natural language processing, sentiment analysis, and network analysis techniques.
The computational findings show that in the pre-crisis phase, the platform prepared the network atmosphere for conflict by applying “preemptive salience” and marginalizing pacifist narratives. At the height of the crisis and at the same time as human users were blocked from communicating, machine actors (bots) filled the agency vacuum with a strategy of space saturation and maximized the “digital silence spiral” by systematically amplifying the feeling of anger (53% of content). In the post-crisis phase, algorithms returned authority to human influencers by creating guided bipolarity to give legitimacy and a lasting identity to machine-generated narratives. The results of this study prove that gatekeeping in the era of big data has changed from human-centered content management to the engineering of emotional and algorithmic infrastructures, and artificial intelligence has become the main architect of public perception with its invisible management of data.